Boor's paper mentions several variants of the Harwayne method. Know
particularly the method used in Table 2 on page 335. To illustrate the method,
let us consider the following practice problem.
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You are setting workers' compensation rates for construction workers in New
York. Your company writes only in New York, New Jersey, and Pennsylvania, and
writes only construction risks and manufacturing risks. You have the following
historical data:
Payroll is in hundreds of thousands of dollars, and indemnity benefits are in thousands of dollars.
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The Indicated Pure Premium
The indicated pure premium is the historical benefit costs divided by the
payroll, or $600,000 ÷ $20,000,000 = $3.00 per $100 of payroll. This
examination question, since it is based on the Boor reading, not the Workers'
Compensation Ratemaking study note, does not ask about partial pure premiums, or
the pure premium for serious losses versus the pure premium for non-serious
losses.
How much credibility should be assigned to this indicated pure premium? The
Boor paper does not discuss the amount of credibility to be assigned to the
figure indicated from historical experience versus the amount of credibility to
be assigned to the complement. Rather, the Boor paper discusses how to determine
the complement. Some candidates are confused by this, so remember: Boor's
examples do not show the final rate indication. They show only the derivation of
the amount which is assigned the complement of credibility.
State Benefit Levels
Harwayne's method at first seem complex. To make the method clear, let us
first solve this problem incorrectly, without first adjusting New Jersey and
Pennsylvania to New York's benefit level.
New Jersey's indicated pure premium for construction workers is
Similarly, Pennsylvania's indicated pure premium for construction workers is
Thus, the overall (countrywide) pure premium, excluding New York, is an
average of the New Jersey and Pennsylvania pure premiums. If we were to take a
pure average, we would get ($5.00 + $1.50) ÷ 2 = $3.25. Since New Jersey has
four times the exposure as Pennsylvania, we might want to take a weighted
average, using the exposures as weights, or
Adjusting the Benefit Levels
What is wrong with these answers? Well, these other states might have
differing benefit levels than New York has. Looking at both construction and
manufacturing workers, we see that New Jersey provides higher average benefits
than New York does, and Pennsylvania provides lower average benefits than New
York does. The benefit levels may differ (i) because of statutory differences
between jurisdictions (e.g., one state's compensation rate may be 65% of
pre-injury wage while another states's may be 70% of pre-injury wage) or (ii)
because of differences in the claim environment (e.g., some states have high
levels of attorney involvement in workers' compensation claims). [The benefit
levels shown here are illustrative only, and do not correspond to actual New
York, New Jersey, and Pennsylvania statutes.]
We adjust New Jersey's and Pennsylvania's benefits payments to the New York
benefit level. To do this, we first complete the spreadsheet to show the totals
for all classes combined in these three states.
| Harwayne's Method | |||||||
| NEAS study aid: Practice Problem | |||||||
| State | Class | Payroll | Benefit | Rate | Reweighted | Reduction Factor |
Adjusted Rate |
| New York | Construction | $200 | $600 | 3.000 | 3.325 | ||
| Manufacturing | $500 | $800 | 1.600 | 1.417 | |||
| Total | $700 | $1,400 | 2.000 | ||||
| New Jersey | Construction | $400 | $2,000 | 5.000 | 3.500 | ||
| Manufacturing | $2,000 | $4,000 | 2.000 | 1.400 | |||
| Total | $2,400 | $6,000 | 2.500 | 2.857 | 0.700 | ||
| Pennsylvania | Construction | $100 | $150 | 1.500 | 2.625 | ||
| Manufacturing | $100 | $100 | 1.000 | 1.750 | |||
| Total | $200 | $250 | 1.250 | 1.143 | 1.750 | ||
We have completed the worksheet just as Boor does on page 335 of his paper.
Boor's exhibit is confusing, because the numbers he shows in the worksheet are
not the numbers that he uses in the Harwayne method. So let us proceed slowly,
showing what figures we actually use.
The State Distribution
The overall benefit level in New York is correctly shown in the exhibit as
$2.00 per $100 of payroll. This figure is determined as total benefits in New
York divided by total payroll, or $1,400,000 ÷ $70,000,000 = $2.00 per $100 of
payroll.
What about New Jersey? The worksheet shows the corresponding calculation,
just as Boor's exhibit shows. Total benefits are $6,000,000, total payroll is
$240,000,000, so the average benefit is $2.50 per $100 of payroll.
What is happening here? Well, the rate for construction workers is higher
than the rate for manufacturing workers in both New York and in New Jersey (and
in Pennsylvania as well), since workplace injuries are more frequent and more
severe for construction workers than for manufacturing workers. New York has two
and a half times as much manufacturing payroll as construction payroll, so the
average rate is slightly closer to the manufacturing rate. New Jersey has five
times as much manufacturing payroll as construction payroll, so the average rate
is much closer to the manufacturing rate.
Harwayne's question is as follows:
If New Jersey had the New York distribution of exposures among its classes,
what would be the New Jersey average rate?
This is the essential question, and its answer is the pivotal number for the
Harwayne method. It is shown in the text of Boor's paper, not in his exhibit. We
show it in the column captioned "reweighted."
For New Jersey, the indicated rates are $5.00 per $100 of payroll for
construction and $2.00 per $100 of payroll for manufacturing. Using the New York
distribution of payroll (not the New Jersey distribution of payroll), the
average New Jersey rate is
Similarly, for Pennsylvania, the indicated rates are $1.50 per $100 of
payroll for construction and $1.00 per $100 of payroll for manufacturing. Using
the New York distribution of payroll (not the Pennsylvania distribution of
payroll), the average Pennsylvania rate is
These figures, for Boor's example, are shown on the bottom of page 11,
labeled PT and PU. Be careful as you review Boor's paper. The PT figure of 3.88
is not related to the 3.88 in the subtotal line for state T. [The similarity of
the numbers is due to the similar exposure distributions in state S and state T
in the paper.]
Reduction Factors
We now ask: "What is the relationship of New York benefit levels to New
Jersey benefit levels?" Well, the average benefits levels are $2.00 in New
York, $2.857 in New Jersey, and $1.143 in Pennsylvania, using the New York
exposure distribution in each state. Therefore, the ratio of New York benefit
levels to New Jersey benefit levels is 0.700 to 1, as shown in the column
captioned "reduction factor" [2.000 ÷ 2.857 = 0.700.] Similarly, the
ratio of New York benefit levels to Pennsylvania benefit levels is 1.750 to 1.
[As before, 2.000 ÷ 1.143 = 1.750.] We call these "reduction
factors," following the terminology of the Workers' Compensation Ratemaking
study note. [There is no term for this in Boor's paper.]
We can now adjust the historical rate levels for construction workers in New
Jersey and in Pennsylvania to the New York benefit levels.
For New Jersey, the indicated rate is $5.00 per $100 of payroll. We
multiply this by the reduction factor of 0.700 to get the
"adjusted" New Jersey rate of $3.500 per $100 of payroll. The
adjusted rate is shown in the column captioned "adjusted rate."
For Pennsylvania, the indicated rate is $1.50 per $100 of payroll. We
multiply this by the reduction factor of 1.750 to get the
"adjusted" Pennsylvania rate of $2.625 per $100 of payroll.
Study Recommendation
"Isn't this a bit complex for an examination problem?" asks the Exam 5 candidate.
On the contrary. Boor spends four pages explaining this procedure, and he
includes a complete example. The Workers' Compensation Ratemaking study note
describes the same procedure, and it is a standard techniques both for workers'
compensation ratemaking and for rate indications in other lines of business. The
mathematics is trivial. However, it is simple to make mistakes, and most
candidates will get it wrong. So memorize the procedure.