THE SATELLITE INSURANCE MARKET
AND UNDERWRITING CYCLES
Piotr Manikowski,
Poznan University of Economics, Poland
Mary Weiss,
Temple University
ARIA Annual Meeting
Quebec City, August 5-8, 2007
Agenda
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2
Introduction
Aims
The satellite insurance industry
Hypotheses
Data
Methodology
Results
Conclusions
Agenda
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Introduction
Aims
The satellite insurance industry
Hypotheses
Data
Methodology
Results
Conclusions
The Underwriting Cycle
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Source: Kunstadter, 2005
Agenda
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Introduction
Aims
The satellite insurance industry
Hypotheses
Data
Methodology
Results
Conclusions
Aims
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Determine whether underwriting cycles exist in
satellite insurance, and the length of the cycle
if relevant.
Determine whether premium components
(rates-on-line and annual industry-wide
coverage availability or both) are cyclic.
Test two prominent underwriting cycle theories,
the rational expectations/ institutional
intervention hypothesis (Cummins and
Outreville, 1987) and the capacity constraint
theory (Winter, 1994) with satellite insurance
industry data.
Agenda
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Introduction
Aims
The satellite insurance industry
Hypotheses
Data
Methodology
Results
Conclusions
Figure 5
Capacity versus Rate-on-line: 1968-2005
25%
1400
Capacity
Minimum Rate
1200
Average Rate
20%
1000
15%
600
10%
400
5%
200
year
8
20
04
20
02
20
00
19
98
19
96
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94
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92
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90
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88
19
86
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84
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82
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80
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78
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76
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74
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72
0
19
70
19
68
0%
million dollars
800
Agenda
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Introduction
Aims
The satellite insurance industry
Hypotheses
Data
Methodology
Results
Conclusions
Hypotheses
Rational
Expectations/
Institutional
Intervention
Hypothesis
Capacity
Constraint
Theory
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Hypothesis 1a:
Rate-on-line is positively associated with past
losses.
Hypothesis 1b:
The maximum amount of coverage available is
negatively related to past losses.
Hypothesis 2:
Satellite insurance rates are inversely related to
the amount of satellite insurance coverage
available.
Hypothesis 3:
Satellite insurance rates and maximum available
coverage are determined simultaneously.
Agenda
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Introduction
Aims
The satellite insurance industry
Hypotheses
Data
Methodology
Results
Conclusions
Data
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Period: 1968 – 2005
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Type of data:
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Satellite insurance underwriting data: claims,
premiums, loss ratios, rates (minimum, maximum,
average) and capacity (the sum of the maximum
amounts that each underwriter is willing to provide
on one satellite for launch and in-orbit insurance);
number of launches; average satellite value
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Reinsurance data: number of reinsurers, surplus
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Macroeconomic data: interest rates, stock prices
Agenda
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Introduction
Aims
The satellite insurance industry
Hypotheses
Data
Methodology
Results
Conclusions
Underwriting Cycle
Determination
–
existence of the underwriting cycle:
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a second-order autoregressive model proposed by
Venezian (1985):
Pt = a0 + a1 Pt-1 + a2 Pt-2 + ωt,
tested variables: the minimum and the average rate,
capacity, and loss ratio
 A cycle is present if a1 > 0, a2 < 0 and (a1)2 + 4a2 < 0
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–
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cycle periods:
T
2
 a1 

cos 
2 a 
2 

1
Hypothesis Testing
Regression models:
–
Satellite insurance rate model:
Ratet    1Loss ratiot 1   2Loss ratiot 2  3Loss ratiot 3
(-)
  4 Capacityt  5 Demandt  6 Interest ratet
(+)
 7 New satellite valuet  8Trend   t
–
Satellite insurance capacity model:
Capacityt    1Loss ratiot 1   2 Loss ratiot 2   3Loss ratiot 3
(-)
 4 Ratet   5Stock pricet   6 Number Re insurerst
 7  Re insurers Surplust   8Trend  t
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(+)
(+/-)
Agenda
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16
Introduction
Aims
The satellite insurance industry
Hypothesis
Data
Methodology
Results
Conclusions
Cycle Test Results for Satellite
Insurance (1968-2005)
Variable
Loss Ratio
Without trenda
Cycle
Period
With trendb
Cycle
Period
No
N/A
No
N/A
Minimum Rate-on-Line
Yes
13.73
Yes
12.36
Average Rate-on-Line
No
N/A
Yes
17.26
Yes
25.85
Yes
10.84
Capacity
a
The OLS equation estimated is Vt=a + a1Vt-1 + a2Vt-2 + et
b
The OLS equation estimated is Vt=a + a1Vt-1 + a2Vt-2 + a3Trend + et
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∆Min. Rate Regression Results
(1972-2005)
OLS Results
Coeff.
t-stat
Intercept
0.0039
0.98
∆Loss Ratio1
0.0086
∆Loss Ratio2
∆Loss Ratio3
-0.0202
-2.27 **
1.98 *
0.0078
2.02 **
0.0126
2.24 **
0.0138
2.35 **
0.0059
1.5
0.0072
1.69 *
-1.93 **
∆Capacity
-0.0002
-3.66 ***
-0.0001
∆Discount rate
-0.0085
-2.46 **
-0.0086
∆No. of Launches
0.0004
0.9
0.0003
0.46
∆New Sat. Value
-0.0001
-0.67
0.0001
0.62
0.0005
1.14
0.0008
1.44
Trend
R-squared
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3SLS Results
Coeff.
z-stat
0.52
-3.2 ***
0.46
∆ Capacity Regression Results
(1972-2005)
OLS Results
Coeff.
t-stat
Intercept
27.03
0.97
25.96
1.08
∆Loss Ratio1
2.02
0.28
2.08
0.19
∆Loss Ratio2
-2.26
-0.21
-1.99
-0.14
∆Loss Ratio3
-1.49
-0.19
-1.42
-0.14
∆Minimum rate
∆Share Price
-1377.29
-3.57 ***
-1465.60
-2.15 ***
0.56
5.37 ***
0.57
4.51 ***
∆No. of Reinsurers
-0.19
-0.09
-0.13
-0.11
∆Reinsurer Surp.
-0.01
-0.39
0.00
-0.71
Trend
-2.82
-1.64
-2.63
R-Squared
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3SLS Results
Coeff.
z-stat
0.64
-1.76 *
0.64
Agenda
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20
Introduction
Aims
The satellite insurance industry
Hypothesis
Data
Methodology
Results
Conclusions
Conclusions (1)
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
Confirmation of the existence of an
underwriting cycle in satellite insurance market
(for minimum rate-on-line, average rate-on-line,
and capacity).
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Cycle periods are relatively long (10 to 25
years) compared to the average six year cycle
commonly cited in other studies.
Conclusions (2)
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Confirmation of the rational expectations/
institutional intervention hypothesis - a positive
and significant relationship between the
minimum-rate-on line and lagged loss ratios.
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Confirmation of the capacity constraint theory the minimum rate-on-line is negatively related
to capacity (coverage availability).
Conclusions (3)
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Because of the unique data used in this study
we are able to determine that the maximum
coverage available in the satellite insurance
industry and the rate-on-line are determined
simultaneously.
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Further, our results suggests, that changes in
capacity appear to be relatively more
responsive to changes in the minimum rate
than the other way around.
THANK YOU FOR
YOUR ATTENTION
Contact:
[email protected]
[email protected]
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