Regulation of Reinsurance Recoverables: Protection or Protectionism?
Cassandra Cole
College of Business, RBA 525
Florida State University
Tallahassee, FL 32306
(850) 644-9283 (phone)
(850) 644-4077 (fax)
Email: ccole@cob.fsu.edu
Kathleen McCullough
College of Business, RBA 150
Florida State University
Tallahassee, FL 32306
(850) 644-8358 (phone)
(850) 644-4077 (fax)
Email: kmccullo@cob.fsu.edu
Lars Powell (contact author)
Department of Economics and Finance
University of Arkansas at Little Rock
2801 S. University Ave.
Little Rock, AR 72204
(501) 569-8894 (phone)
(501) 569-8871 (fax)
Email: lspowell@ualr.edu
Working draft
July 6, 2006
THIS DRAFT IS PRELIMINARY.
PLEASE DO NOT CITE WITHOUT THE AUTHORS’ PERMISSION
Abstract:
Under current insurance regulations, U.S. insurers are required to calculate the provision
for reinsurance which decreases statutory assets to reflect the possibility that a portion of
reinsurance recoverables may be uncollectible. To avoid this penalty, unauthorized
reinsurers must fully collateralize gross U.S. liabilities. U.S. insurance regulators and
alien reinsurers continue to debate the appropriateness and efficacy of current
collateralization requirements. Regulators view the collateralization requirements as
necessary to protect U.S. consumers, given the differences in accounting practices and
regulatory legal authority in the U.S. and abroad. Alien reinsurers claim the
collateralization requirements impose unjustified costs on some financially secure
reinsurers, effectively limiting market capacity. We measure the impact of insurers’
balance sheet entries of the provision for unauthorized reinsurance on the price of
insurance. This provides an initial test of the market’s valuation of uncollateralized
reinsurance recoverables from unauthorized reinsurers. Results are consistent with a
negative relation between the use of unauthorized reinsurance and price, suggesting the
required collateralization of recoverables provides important protection for U.S. insurers
and insurance consumers.
Regulation of Reinsurance Recoverables: Protection or Protectionism?
Abstract
Under current insurance regulations, U.S. insurers are required to calculate the provision
for reinsurance which decreases statutory assets to reflect the possibility that a portion of
reinsurance recoverables may be uncollectible. To avoid this penalty, unauthorized
reinsurers must fully collateralize gross U.S. liabilities. U.S. insurance regulators and
alien reinsurers continue to debate the appropriateness and efficacy of current
collateralization requirements. Regulators view the collateralization requirements as
necessary to protect U.S. consumers, given the differences in accounting practices and
regulatory legal authority in the U.S. and abroad. Alien reinsurers claim the
collateralization requirements impose unjustified costs on some financially secure
reinsurers, effectively limiting market capacity. We measure the impact of insurers’
balance sheet entries of the provision for unauthorized reinsurance on the price of
insurance. This provides an initial test of the market’s valuation of uncollateralized
reinsurance recoverables from unauthorized reinsurers. Results are consistent with a
negative relation between the use of unauthorized reinsurance and price, suggesting the
required collateralization of recoverables provides important protection for U.S. insurers
and insurance consumers.
1. Introduction
U.S. insurance regulators and reinsurers, alien reinsurers in particular, continue to debate
the appropriateness and efficacy of current collateralization requirements imposed on
“unauthorized” reinsurers participating in U.S. markets.1 In the U.S., a reinsurer is
deemed “authorized” if it adequately subjects itself to the domiciliary state’s jurisdiction.2
Any reinsurer that does not meet this criterion is considered “unauthorized.” While some
U.S. reinsurers are unauthorized, the majority of unauthorized reinsurers are licensed
outside the U.S.
Monitoring insurer solvency is arguably the most important function of insurance
regulators.
Most aspects of solvency regulation involve only primary insurers and
regulators. However, given the increasing role of reinsurance recoverables in primary
1
2
See NAIC (2006), Levene (2006) and Wojcik and Fletcher (2003) for detailed discussion of these issues.
Criteria for authorization are described in detail in Section 2.
3
insurers’ capital structures, regulators also are concerned with the financial strength of
reinsurers. 3
Global diversification of reinsurance markets presents challenges in regulating
reinsurers’ financial conditions.
Some of the world’s major reinsurers are licensed
outside the U.S., beyond the direct authority of U.S. regulators. To ensure the prompt
payment of reinsurance recoverables, U.S. regulators require unauthorized reinsurers to
fully collateralize amounts due to U.S. insurers via letters of credit or other means from
U.S. financial institutions.4 This requirement is imposed indirectly by subjecting U.S.
licensed insurers to Credit for Reinsurance laws. Under these laws, a primary insurer
with recoverables from an unauthorized reinsurer must reduce its statutory assets by the
amount recoverable that is not fully collateralized. This reduction in assets is part of a
balance sheet liability item called the provision for unauthorized reinsurance (PFUR).5
Collateralization of recoverables, via letters of credit or other allowable means,
creates transaction costs. Parties promoting change in the Credit for Reinsurance laws,
primarily unauthorized alien reinsurers, argue this is protectionism in favor of U.S.
reinsurers. Opponents of reforming these laws claim the collateralization requirements
are necessary to the financial strength of domestic primary insurers given differences in
accounting methods and enforceability of contracts in other countries.
3
On December 31, 2004, reinsurance recoverables totaled over US$240 billion or 59.3 percent of U.S.
insurer surplus (NAIC, 2006).
4
Other methods of collateralization include establishing a trust and providing some other form of
acceptable security with trusts and letters of credit being the most common. These two methods are
discussed in more detail later.
5
The provision for unauthorized reinsurance is actually part of a larger charge known as the provision for
reinsurance. The portion attributed to unauthorized reinsurance is the larger of the two components of the
provision for reinsurance accounting for more than 70 percent of the average industry charge.
Approximately 88 percent of the insurers reporting a provision for reinsurance report this component. The
other component of the charge is the provision for overdue authorized reinsurance. Given the relative
magnitude of the provision for unauthorized reinsurance relative to the other component, this study focuses
on this area.
4
We provide insight into this argument by assessing the market’s valuation of
uncollateralized reinsurance recoverables from unauthorized reinsurers. Specifically, we
test the effect of the PFUR on the price of insurance. The PFUR is an adjustment to
statutory assets. It does not directly affect cash flows. If insurance consumers do not
believe uncollateralized recoverables pose a threat to insurer solvency, the price of
insurance should display a non-negative relation to the provision for reinsurance.
Alternatively, a negative relation between the provision for reinsurance and price
suggests that the collateralization of recoverables provides valuable assurance that
unauthorized reinsurers will meet their U.S. obligations. This paper makes substantial
contributions to the literature in the areas of international insurance regulation, insurer
solvency, and insurer capitalization. To our knowledge, analysis of the provision for
reinsurance in the academic literature is largely absent.
2. Background
Purchasing reinsurance affects insurer solvency because it is essentially a capital
structure decision, with equity capital and reinsurance acting as substitutes (Berger,
Cummins, and Tennyson, 1992; Garven and Lamm-Tennant, 2003).
Therefore,
insurance regulators must consider the quality of reinsurance purchased by U.S. insurers
when assessing their financial strength. Cole and McCullough (2006) find that of the
insurers utilizing foreign reinsurance, the average amount ceded to a foreign reinsurance
is about 19 percent, with about 16 percent of that being ceded to firms not affiliated with
the cedent. This presents a challenge when regulating the solvency of cedents because
U.S. regulators have no direct authority to monitor or control alien reinsurers. Further,
5
accounting rules and contract law in other jurisdictions differ from that of the U.S.,
creating potential uncertainty in the cedent’s ability to collect amounts due from alien
reinsurers. To mitigate the potential adverse effects on domestic insurers’ financial
strength, U.S. regulators in every state enforce Credit for Reinsurance laws on domestic
ceding insurers.
Credit for Reinsurance laws require U.S. insurers to fully collateralize all amounts
recoverable from “unauthorized” reinsurers. In the U.S., an “authorized” reinsurer meets
one of the three following criteria: 1) it is licensed in the ceding insurer’s domiciliary
state to write the type of insurance being ceded; 2) it is an accredited reinsurer in the
ceding insurer’s state of domicile; or 3) it is given regulatory equivalence by being
licensed in a state with substantially similar reinsurance regulation as the ceding insurer’s
domicile (NAIC, 2006). If a reinsurer does not meet at least one of these criteria, it is
considered “unauthorized.” While there is no regulation preventing a U.S. insurer from
ceding reinsurance to any other company anywhere in the world, a cedant must obtain
full collateralization of the reinsurer’s liabilities to receive credit for cessions to an
unauthorized reinsurer in its statutory financial statement.
These liabilities, called
reinsurance recoverables, include paid losses; paid loss adjustment expenses (LAE);
unearned premium reserves (known case loss and LAE reserves); incurred but not
reported (IBNR) loss and LAE reserves; and contingent commissions.
Collateralization of recoverables provides domestic insurers and regulators a
direct means of collecting amounts due from unauthorized reinsurers regardless of
accounting rules and contract law governing the reinsurer’s licensing jurisdiction.
Collateral may be posted in several acceptable forms. While there are others, the most
6
common methods of collateralization are letters of credit (LOC) and trusts. The LOC
must be issued or confirmed by a qualified U.S. financial institution. Terms of the LOC
make performance dependent only on the solvency of the issuing bank without regard to
the financial condition or willingness to pay of the reinsurer. An unauthorized reinsurer
also may establish a trust with individual or multiple beneficiaries which accomplishes
the same general outcome as a LOC.
Collateralization requirements subject unauthorized reinsurers to transaction costs
not imposed on authorized reinsurers. Estimates of these transaction costs range from
fifteen to sixty basis points, and the sum of these costs for all unauthorized reinsurers is
estimated to be between $200 million and $500 million per year (NAIC, 2006).
Proponents of reforming Credit for Reinsurance laws claim the current regulation gives
authorized reinsurers an unfair advantage in the market for U.S. cessions. They propose
an amendment decreasing the collateralization requirement for certain unauthorized
reinsurers displaying exceptional financial strength and a history of integrity.
U.S.
insurance regulators and some primary insurers argue collateralization requirements are
important to domestic insurer solvency and facilitate smaller primary insurers’ access to
international reinsurance markets (Wojcik and Fletcher, 2003).
3. Variables and Hypotheses Development
In this paper, we investigate the appropriateness and efficacy of Credit for Reinsurance
Laws by estimating the relation between the PFUR and the price of insurance. Sommer
(1996) shows the price of insurance is negatively correlated with insolvency risk.
Therefore, if the PFUR is related to increases in insolvency risk, it should exhibit a
7
negative relation to price.
Conversely, if collateralization requirements decrease
insolvency risk or do not affect insolvency risk, the relation between price and the PFUR
should be non-negative.
The variables used in our empirical tests are defined in Table 1. Our dependent
variable is the inverse of the economic loss ratio and proxies the price of insurance. 6 It is
the ratio of real premium written net of underwriting expenses and policyholder
dividends to the present value of real incurred losses and loss adjustment expenses.
Liabilities are discounted to present value using interest rates and payout tails prescribed
by the Internal Revenue Service.
[Table 1 here]
PFUR is the independent variable of primary interest in our analysis. The PFUR
measure is taken from the Footnote of Part 7 of Schedule F of the National Association of
Insurance Commissioners (NAIC) Property-Casualty financial statements.
In the
following empirical tests, the PFUR is scaled by net premiums written.
Several other firm specific factors are hypothesized to affect the price of
insurance.
Specifically, we control for firm size, underwriting leverage, group
membership, organizational form, concentration of underwriting exposure, and business
mix. Sommer (1996) finds that size and capitalization are positively related to price.
Additionally, the insurer solvency literature finds that larger insurers and insurers with
lower leverage are less likely to default (Barniv and Hershbarger, 1990; Carson and Hoyt,
1995; and others).
We measure size as the natural logarithm of firm assets.
6
Similar price measures appear in Winter (1994); Sommer (1996); Chidambaran, Pugel, and Saunders
(1997); Cummins and Danzon (1997); and Weiss and Chung (2004).
8
Underwriting leverage is the ratio of premium written to surplus. All else equal, we
expect larger insurers and insurers with lower leverage to command higher prices.
The majority of insurance companies are members of insurer groups or holding
companies. For example, in 2003, 1,863 of the 2,699 total U.S. property-liability insurers
were members of insurer groups, accounting for more than two-thirds of all insurance
premiums written in the U.S.
Powell and Sommer (2005) show that reinsurance
transacted among affiliates is significantly different from other reinsurance transactions.
A binary variable equal to one if a firm is affiliated with other insurers and zero otherwise
is included in the model to control for differences in reinsurance markets within groups
compared to external reinsurance markets.
Our sample includes insurers organized as stock companies and mutual
companies. Stock companies are owned by equity holders, while mutual companies are
owned by policyholders.
A large body of literature investigates differences across
insurers based on organizational form, finding significant differences.
Specifically,
agency theory suggests stock companies and mutual companies will participate in
significantly different activities. To control for these differences we include a binary
variable equal to one if an insurer is organized as a stock company, and equal to zero
otherwise.
The next two variables measure concentration of underwriting exposure by
geographic area and line of business.
Geographic concentration is measured by a
Herfindahl index of net premiums written by state and line-of-business concentration is
measured by a Herfindahl index of net premiums written by line of business. All else
equal, insurers that concentrate premiums, either by geographic areas or lines of business,
9
are expected to have more exposure to catastrophic loss and consequently receive a lower
price for insurance. However, insurers that concentrate exposures in fewer lines of
business or fewer geographic areas may choose less risky lines of business, or select less
risky insureds within each line or area. Further, these firms may achieve economies of
scale through added focus that allows a lower price structure.
Finally, some lines of insurance differ by expected volatility of cash flows and
levels of competition in markets for specialized covers. It follows that these differences
among lines would lead to substantial variations in price.7 The percentage of premiums
written in each line for each insurer is added to the regression model to control for
business mix.8
4. Data and Methodology
Data Description
The data used are from the National Association of Insurance Commissioners PropertyCasualty Database for the years 2001 through 2004.9 Companies with non-logical values
such as non-positive values for assets, liabilities, surplus, losses or premiums are
excluded. The final sample of firms contains 5,903 observations with 1,932 unique
firms.
Of the full sample of firms more than 25 percent reported a provision for
unauthorized reinsurance. Table 2 provides a summary of the average PFUR for each
7
Note that the dependent variable controls for size and timing of cash flows.
One line of business is omitted to avoid singularity in the model. In addition, one limitation of these data
is that premiums written by line of business do not account for within-line policy heterogeneity. For
example, NAIC data does not differentiate among homeowners policies, even though the risk insured by a
homeowners policy (from wind and hail) in Florida is significantly greater than a policy insuring an
identical home in Minnesota.
9
The detailed information related to the provision for reinsurance was not readily available in the database
prior to 2001.
8
10
year for both the total sample and the subset of firms reporting a PFUR. While the
average percentage of insurers reporting this charge remains fairly stable during the
sample period, the average PFUR drops significantly in the more recent years of the
sample.
[INSERT TABLE 2 HERE]
Methodology
Given that a large portion of insurers do not report a provision for unauthorized
reinsurance, it is important to better understand the nature of this subset of firms relative
to other insurers. In addition, it is important to control for these differences in empirical
modeling that assesses the relation of price and the provision for reinsurance. Further, it
is likely that the size of the provision for unauthorized reinsurance is not exogenous to
price. As such, a single equation framework for instrumental variables as described in
Wooldridge (2002) is employed.
This framework uses the predicted values of the
endogenous PFUR variable as an instrument for PFUR in a single equation framework to
determine whether, when controlling for other factors, the provision for unauthorized
reinsurance has a significant relation on price.10 The model estimated is shown below.
PFURit =  +   Xit +   % FOREIGNit + it
Eq. (1)
PRICEit=  +  (PFURit = PFURHATit) +   Xit + it
Eq. (2)
where,
PFUR
= the provision for unauthorized reinsurance scaled by
net premiums written for insurer i in year t;
10
See Wooldridge (2002) or the description of the IVREG2 procedure in STATA for further details on the
econometric procedure utilized.
11
X
= a vector of exogenous financial and operational
factors controlling for the size of the provision for in
equation (1) and variation in price equation (2) for
insurer i in year t;
% FOREIGN =
the percentage of premiums ceded to foreign
reinsurers by insurer i in year t;
PRICE = the inverse of the economic loss ratio for the
insurer i during year t; and
PFURHAT = the predicted values of the PFUR variable(s) in
equation 1 for insurer i in year t used as instrument for
these variable(s).
The PFURHAT estimate(s) from equation (1) provides a nonlinear function of
PFUR that is not perfectly correlated with the original variable, thus it can be utilized as
an instrument. Though the use of an additional exogenous variable(s) in equation (1) is
not technically required, it is normally justified. In this case, the percentage of premiums
ceded to foreign reinsurers is utilized. Given the large percentage of firms for which the
provision for unauthorized reinsurance is zero, a Tobit model is utilized to estimate
equation (1). The exogenous financial and operational controls, X, utilized in both
equations (1) and (2) include the firm size, group membership, organizational form,
underwriting leverage, concentration of underwriting exposure, and business mix.
As mentioned earlier, price is defined as the inverse of the economic loss ratio, or
net premiums written to the present value of accident year incurred losses adjusted for
underwriting expenses, loss adjustment expenses, and dividend payments. 11
The
provision for unauthorized reinsurance measure is taken from the Footnote of Part 7 of
Schedule F of the NAIC Property-Casualty financial statements.
In the following
empirical tests, the provision for unauthorized reinsurance is scaled by net premiums
11
For a detailed discussion of the benefits of using economic loss ratios as well as constructing the ratio see
Winter (1994); Sommer (1996); Chidambaran, Pugel, and Saunders (1997); Cummins and Danzon (1997);
and Weiss and Chung (2004).
12
written. Table 3 provides summary statistics for the variables included in the model.
Also of concern is the potential heteroskedasticity across firms as well as intragroup correlations among company observations. To control for variation in errors
across firms, the cluster option is used.12 This technique corrects for the presence of
arbitrary heteroskedasticity as well as intra-group correlation that may exist due to
differences across insurers. Tests did not indicate the presence of multicollinearity.
Tests of the price variable reveal the presence of extreme outliers. As a result, the
variable is windsorized at the first and ninety-ninth percentiles. This windsorized price
variable, or inverse economic loss ratio, is used in all estimation models. For the same
reason, the provision for unauthorized reinsurance variable also is windsorized at the first
and ninety-ninth percentiles.
[INSERT TABLE 3 HERE]
5. Results
Given that only about 25 percent of all insurers report a PFUR, initial testing is conducted
to assess whether these firms are statistically different from those not reporting a PFUR.
Table 3 provides summary statistics for the full sample of firms as well as the subsets of
firms reporting and not reporting a PFUR. The table also shows the characteristics for
which firms with and without PFURs are statistically different based on means
comparisons. The results of the means comparisons indicate that, on average, firms
reporting a PFUR have statistically lower prices. In addition, all of the operational and
financial characteristics of firms with a positive provision for unauthorized reinsurance
and those without were statistically different. Specifically, firms with positive values for
12
Due to the presence of several time-invariant variables, the cluster analysis was preferred over a firm
fixed-effects model.
13
the provision for unauthorized reinsurance are larger; more likely group members and
stock companies; and are less concentrated in lines of business and geographic area.
Finally, they more highly leveraged in terms of underwriting leverage and utilize more
foreign reinsurance.
Results from the instrumental variables regression model are presented in Table
4.13 The primary variable of interest, the provision for unauthorized reinsurance, exhibits
a negative relation to price. This result suggests that insurers with larger provisions for
unauthorized reinsurance may be at greater risk for insolvency as reflected in the price
consumers are willing to pay for the coverage.
In addition to the negative and significant coefficient estimate on the variable of
interest, several of the control variables are significant.
Specifically, firm size is
positively related to price and underwriting leverage is negatively related to price. As
noted in the insolvency literature, these firms are less likely to default. As such, they are
potentially able to demand higher prices.
The coefficient estimate for the stock dummy variable is both positive and
significant suggesting that organizational form is related to price. The line-of-business
concentration variable also displays a positive relation to price. This result suggests that
insurers concentrating in lines of business may underwrite less risky exposures within
each line and/or are able to achieve greater economies of scale through focus. Finally,
several of the line-of-business control variables are significant indicating that price is not
uniform across lines of business.
13
As discussed above, in order to control for the potential endogeniety between the PFUR and price an
instrumental variables framework is used. This estimate is used as an instrument in the results presented in
Table 4. The results of the Tobit model used to create an estimated PFUR for each firm can be found in
Appendix.
14
6. Conclusions
Regulation of reinsurance recoverables via provision for reinsurance laws has drawn
renewed criticism from unauthorized alien reinsurers in recent years. These proponents
of change claim that regulatory collateralization requirements are a form of protectionism
favoring U.S. domiciled reinsurers. U.S. regulators and insurance industry advocates
argue that collateralization of reinsurance recoverables from unauthorized reinsurers is an
important tool for mitigating domestic insurer insolvency.
In this paper, we investigate the role of collateralization requirements by
estimating the effect of domestic insurers’ reported PFUR on the price their consumers
pay for insurance. To our knowledge, this is the first academic study to address the
efficacy of collateralization requirements.
We find that, on average, firms reporting a PFUR are significantly different in
terms of operational and financial characteristics than those not reporting a PFUR. Given
that many of these differences also may impact price, we control for potential endogineity
with a single equation instrumental variables approach. In this framework, the predicted
PFUR, which is estimated using a Tobit equation, is used as an instrument for PFUR.
Results from the IV model indicate the PFUR has a negative effect on the price of
insurance. This finding suggests Credit for Reinsurance laws provide valuable protection
for U.S. insurers accessing international reinsurance markets. As with prior, literature the
results confirm that various operational and financial characteristics of the firms also
impact price.
15
In addition to the issues outlined above, there are still several empirical issues that
should be explored on this topic. For example, the current analysis does not separate out
the potential differences in the impact of and utilization of the PFUR based on whether
the firm is a primary insurer or reinsurer. Further, the current version of the paper does
not fully explore the determinates of the use of uncollateralized unauthorized reinsurance.
While the results of the Tobit model do provide some initial evidence, a more complete
analysis should be included. Finally, It is important to note we do not directly address
efficacy of the regulatory changes proposed by Lloyd’s and other large alien reinsurers.
Our analysis assesses all reinsurers reporting PFUR collectively. Further analysis is
required to fully evaluate the proposal to reduce collateralization requirements for
financially strong alien reinsurers.
16
References:
BarNiv, R. and Robert A. Hershbarger, 1990, “Classifying Financial Distress in the Life
Insurance Industry,” Journal of Risk and Insurance, v57: 110-136.
Berger, Lawrence A., J. David Cummins, and Sharon Tennyson, 1992. “Reinsurance and
the Liability Crisis,” Journal of Risk and Uncertainty, v5 (1992): 253-272.
Carson, James M. and Robert E. Hoyt, 1995, “Life Insurer Financial Distress:
Classification Models and Empirical Evidence,” Journal of Risk and Insurance,
v62: 764-775.
Chidambaran, N. K., Thomas Pugel, Anthony Saunders, 1997. “An Investigation of the
Performance of the U.S. Property-Casualty Insurance Industry,” Journal of Risk
and Insurance, v64: 371-381
Cole, Cassandra and Kathleen McCullough, 2006. “A Reexamination of the Corporate
Demand for Reinsurnace,” Journal of Risk and Insurance, v73: 169-192.
Cummins, J. David and Patricia Danzon, 1997, “Price Shocks and Capital Flows in
Liability Insurance,” Journal of Financial Intermediation, v6 n1: 3-38.
Cummins, J. David and David W. Sommer, 1996, “Capital and Risk in Property-Liability
Insurance Markets,” Journal of Banking and Finance v20, n6 (July 1996): 106992
Garven, James R. and Joan Lamm-Tennant. “Demand for Reinsurance: Theory and
Empirical Tests,” Assurances, v7 n3 (July, 2003): 217-238.
Grace, Elizabeth V., 1990. “Property-Liability Insurer Reserve Errors: A Theoretical and
Empirical Analysis,” Journal of Risk and Insurance, 57: 28-46.
17
Harrington, Scott E. and Patricia Danzon, 1994. “Price Cutting in Liability Insurance
Markets,” Journal of Business, v67, n4: 511-538
Levene, Peter, 2006. “Handcuffs on ‘Aliens,’” The Wall Street Journal, February 6, 2006
Mayers, David and Clifford W. Smith, 1990. “On the Corporate Demand for Insurance:
Evidence from the Reinsurance Market,” Journal of Business, 63: 19-40.
NAIC, 2006. U.S. Reinsurance Collateral White Paper, NAIC Reinsurance Task Force
(Kansas City, MO, 3/05/2006)
Petroni, K. R., 1992. “Optimistic Reporting in the Property-Casualty Insurance Industry,”
Journal of Accounting & Economics, 15: 485-508
Powell, Lawrence S. and David W. Sommer, 2005, “Internal versus External Capital
Markets in the Property-Liability Insurance Industry: The Role of Reinsurance,”
SSRN Risk Management Working Paper Series, March, 2005. Available from
http://ssrn.com/abstract=664626.
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Prices,” Journal of Risk and Insurance, (September) v63 n3: 501-514
Weiss, M. A. and J. Chung, 2004. “U.S. Reinsurance Prices, Financial Quality, and
Global Capacity,” Journal of Risk and Insurance, 71: 437-467
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Financial Intermediation 3, 379-415
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Change,” Business Insurance, v37n35: 10-16. September 1, 2003
18
Table 1 – Definitions of Variables
Variable
Provision for Unauthorized Reinsurance*
Definition
Amount of reinsurance
recoverables not fully
collateralized
Price*
The ratio of real premium written
net of underwriting expenses and
policyholder dividends to the
present value of real incurred
losses and loss adjustment
expenses
Size
Natural logarithm of firm assets
Affiliated Dummy Variable
Dummy variable equal to one if
the firm is affiliated and zero
otherwise
Stock Dummy Variable
A dummy variable equal to one if
the firm is organized as a stock
company and zero otherwise (note
that the only other organizational
form included is mutuals)
Direct Business to Surplus
Ratio of direct premiums written
to policyholder surplus
Line-of-Business Concentration
Herfindahl index of net premiums
written by line of business
Geographic Concentration
Herfindahl index of net premiums
written by state
Alien Reinsurance
Percentage of premiums ceded to
alien reinsurers
* Indicates variables windsorized at one percent and 99 percent.
19
Table 2 – Summary Statistics for the Provision for Unauthorized Reinsurance
Panel A: Full Sample
Year
2001
2002
2003
2004
Observations
1613
1594
1525
1165
Mean PFUR
$ 2,112,035
$ 2,321,624
$ 1,975,702
$ 1,260,605
Panel B: Firms Reporting PFUR
2001
2002
2003
2004
405
395
399
301
$
$
$
$
8,411,638
9,368,780
7,551,241
4,879,086
20
Table 3 – Summary Statistics
Panel A: Full Sample
Variable
Provision for Unauthorized Reinsurance^
Price^
Size
Affiliated Dummy Variable
Stock Dummy Variable
Direct Business to Surplus
Line-of-Business Herfindahl Index
Geographic Herfindahl Index
Alien Reinsurance
Obs
Mean
Std. Dev.
Min
Max
5903 0.01285
0.06792 0.00000
0.56636
5903 1.19781
0.79568 0.01059
6.26845
5903 18.08717
1.95899 12.84504
25.17813
5903 0.68558
0.46432 0.00000
1.00000
5903 0.74792
0.43424 0.00000
1.00000
5903 7.95443 118.73250 0.00000 5678.72700
5903 0.67945
0.28423 0.17076
1.00000
5903 0.60762
0.37977 0.03242
1.00000
5903 0.13524
0.25383 0.00000
1.00000
Panel B: PFUR>0 Sample
Provision for Unauthorized Reinsurance^*
Price^*
Size*
Affiliated Dummy Variable*
Stock Dummy Variable*
Direct Business to Surplus*
Line-of-Business Herfindahl Index*
Geographic Herfindahl Index*
Alien Reinsurance*
1506 0.05037
1506 1.14902
1506 19.51946
1506 0.86189
1506 0.79681
1506 2.46439
1506 0.58944
1506 0.42531
1506 0.23129
0.12728 0.00000
0.63278 0.01059
1.74721 14.63412
0.34513 0.00000
0.40250 0.00000
8.92071 0.00000
0.27446 0.17076
0.36872 0.03242
0.28681 0.00000
0.56636
6.26845
24.66073
1.00000
1.00000
283.06940
1.00000
1.00000
1.00000
Panel C: PFUR=0 Sample
Provision for Unauthorized Reinsurance^*
Price^*
Size*
Affiliated Dummy Variable*
Stock Dummy Variable*
Direct Business to Surplus*
Line-of-Business Herfindahl Index*
Geographic Herfindahl Index*
Alien Reinsurance*
4397 0.00000
0.00000 0.00000
0.00000
4397 1.21452
0.84369 0.01059
6.26845
4397 17.59660
1.77868 12.84504
25.17813
4397 0.62520
0.48413 0.00000
1.00000
4397 0.73118
0.44340 0.00000
1.00000
4397 9.83481 137.42580 0.00000 5678.72700
4397 0.71027
0.28097 0.18952
1.00000
4397 0.67006
0.36305 0.03292
1.00000
4397 0.10234
0.23259 0.00000
1.00000
^ Indicates variables windsorized at one percent and 99 percent; *Indicates means statistically different at
10 percent or better.
21
Table 4 – Results of IV Regression
Variable
Constant
Provision for Unauthorized Reinsurance^
Size
Affiliated Dummy Variable
Stock Dummy Variable
Direct Business to Surplus
Line-of-Business Herfindahl Index
Geographic Herfindahl Index
Fire
Allied Lines
Ocean Marine
Earthquake
Aircraft
Burglary and Theft
Boiler and Machinery
Financial Guaranty
Fidelity
Surety
Credit
Medical Malpractice - Occurrence
Medical Malpractice - Claims Made
Other Liability - Occurrence
Other Liability - Claims Made
Product Liability - Occurrence
Product Liability - Claims Made
Workers Compensation
Private Passenger Auto Liability
Commercial Auto Liability
Auto Physical Damage
Homeowners Multiple Peril
Farmers Multiple Peril
Group Accident and Health
Other Accident and Health
Reinsurance - Property
Reinsurance - Liability
Reinsurance - Financial Lines
2002 Year Dummy
2003 Year Dummy
2004 Year Dummy
Observations
Robust standard errors
* significant at 10%; ** significant at 5%; *** significant at 1%
Coefficient
0.039
-4.8991
0.0519
-0.0463
0.1234
-0.0001
0.5428
0.0045
-0.0715
-0.1661
0.1494
0.8198
0.7493
0.8953
0.5875
2.3123
2.0819
0.0233
-0.3845
-0.4349
-0.4302
-0.228
-0.3044
1.1927
-0.2685
-0.4404
-0.5741
-0.2216
-0.4146
-0.2824
-0.2495
-0.5688
0.1958
-0.0623
-0.2309
-3.5527
0.1252
0.1641
0.2667
5903
Std. Err.
0.4164
2.7730*
0.0202**
0.0375
0.0345***
0.0000**
0.0928***
0.0439
0.1948
0.2405
0.4530
0.9761
0.6930
1.2858
0.6429
0.6492***
0.8278**
0.2278
0.3233
0.3037
0.1544***
0.1611
0.1577*
0.4063***
0.3435
0.1422***
0.1681***
0.1847
0.1516***
0.1410**
0.1928
0.1794***
0.4007
0.4650
0.2848
5.0498
0.0205***
0.0221***
0.0507***
22
Appendix – Results of Tobit Model
Variable
Coefficient
Std. Err.
Constant
-0.7368
0.0384 ***
Size
0.0303
0.0017 ***
Affiliated Dummy Variable
0.0550
0.0076 ***
Stock Dummy Variable
0.0064
0.0069
Direct Business to Surplus
-0.0005
0.0003 *
Line-of-Business Herfindahl Index
-0.0009
0.0111
Geographic Herfindahl Index
-0.0321
0.0080 ***
Alien Reinsurance
0.1256
0.0097 ***
Fire
0.0088
0.0260
Allied Lines
0.0377
0.0316
Ocean Marine
0.1496
0.0365 ***
Earthquake
0.3133
0.0925 ***
Aircraft
0.2285
0.0540 ***
Burglary and Theft
0.5236
0.1276 ***
Boiler and Machinery
0.1875
0.0717 ***
Financial Guaranty
-0.0761
0.0394 *
Fidelity
0.2643
0.1041 **
Surety
0.0391
0.0213 *
Credit
-0.0276
0.0400
Medical Malpractice - Occurrence
-0.0877
0.0425 **
Medical Malpractice - Claims Made
0.0268
0.0199
Other Liability - Occurrence
0.0334
0.0204
Other Liability - Claims Made
0.0867
0.0214 ***
Product Liability - Occurrence
0.1742
0.0780 **
Product Liability - Claims Made
-0.1082
0.1143
Workers Compensation
0.0039
0.0164
Private Passenger Auto Liability
-0.1153
0.0211 ***
Commercial Auto Liability
0.0674
0.0230 ***
Auto Physical Damage
0.0498
0.0228 **
Homeowners Multiple Peril
-0.0021
0.0193
Farmers Multiple Peril
0.1103
0.0497 **
Group Accident and Health
-0.0228
0.0330
Other Accident and Health
0.1216
0.0315 ***
Reinsurance - Property
0.0744
0.0526
Reinsurance - Liability
-0.0633
0.0569
Reinsurance - Financial Lines
0.6389
0.8295
2002 Year Dummy
-0.0027
0.0070
2003 Year Dummy
-0.0043
0.0071
2004 Year Dummy
0.0270
0.0078 ***
Sigma
0.1371
0.0026
* significant at 10%; ** significant at 5%; *** significant at 1%
23