D-1

APPENDIX D: ESTIMATION OF THE DISTRIBUTOR/WHOLESALER AND

DEALER/CONTRACTOR MARKUPS ON INCREMENTAL CENTRAL AIR

CONDITIONER AND HEAT PUMP COSTS

D.1 INTRODUCTION

The markup on incremental cost increases is an important factor in estimating the price

consumers pay for central air conditioners and heat pumps after a change in the minimum efficiency

standard. For the central air conditioner and heat pump rulemaking, direct information on the

incremental markup on equipment costs for higher efficiency units is not readily available. This is

partially due to the fact that such units are often included in the construction costs of new housing

or as a package that includes installation. In addition, because higher efficiency units may have

different markups than baseline units at minimum efficiency and higher efficiency units are not

produced at the same volume as baseline units, current incremental equipment costs observed in the

market may not be representative of the incremental costs under a new standard.

In the analysis for the Supplemental Advance Notice of Proposed Rulemaking (ANOPR),

manufacturer costs for the higher efficiency equipment under a new standard were estimated, and

the consumer costs were obtained by applying markups at the different steps of the distribution chain

to arrive at the final consumer cost. The distribution chain markup consists of a markup on

incremental manufacturing costs applied by the manufacturers, a distributor/wholesaler markup

applied by distributors and wholesalers, a dealer/contractor markup applied by dealers and HVAC

contractors and a markup for sales tax. For the new housing market, a markup is also applied by

housing developers and builders. The markups applied in the Supplemental ANOPR analysis for

distributor and dealer markups were determined from aggregate average markups for the businesses

in the distribution chain. This means at each stage of distribution, direct costs of sales, i.e.,

purchased equipment and materials and direct labor costs, were compared with the total volume of

business revenues, and the ratio of total business revenues to direct costs was used to determine the

markup. 

The analysis detailed here for the Notice of Proposed Rulemaking (NOPR) examined the

scaling behavior of markups for wholesalers and contractors, and determined that markups are

neither fixed-dollar, nor proportional to all direct costs, but somewhere in-between. Using the

available data, we have found measurable differences between incremental markups on direct

equipment costs and the average aggregate markup on direct business costs. Significant differences

were found between average and incremental markups for heating, ventilation, air-conditioning and

refrigeration (HVACR) wholesalers/distributors, and for HVAC dealers/contractors. Section D.3

further discusses the differences between average and incremental markups.

Table D.1 provides a comparison of the markups used in the analysis for the NOPR and those

which were used in the Supplemental ANOPR. 

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Table D.1 Comparison of Revised Markups and Supplemental ANOPR Markups

NOPR Supplemental ANOPR

Type Markup Markup

Manufacturer Markup 1.23 1.18

Wholesaler/Distributor Markups

10 SEER 1.37

1.37

11 SEER 1.33

12 SEER 1.30

13 SEER 1.26

18 SEER 1.21

Dealer/Contractor

Equipment Markup 1.27 1.55

Installation Labor

Air Conditionersa $1,279 / $1,367 $1,190

Heat Pumpsa $2,280 / $2,160 $2,035

Builder Markup 1.09b 1.00c

Sales Tax 1.04b 1.07d

Overall Markup

10 SEER 2.42 2.68

11 SEER 2.36 2.68

12 SEER 2.30 2.68

13 SEER 2.24 2.68

18 SEER 2.14 2.68

a For revised analysis, first value pertains to split systems and second value pertains to single package systems.

b Weighted-average markups representing both the new construction and replacement markets.

c For the Supplemental ANOPR, builder markups were not considered.

d For the Supplemental ANOPR, sales taxes representing only the replacement market were used.

Table D.2 shows the effect that the revisions have on the consumer’s total installed price for

split system air conditioners at efficiency levels ranging from 10 to 13 SEER.

Table D.2 Total Installed Price Comparisons – Split Air Conditioners

Efficiency Level NOPR Supplemental ANOPR Change

10 SEER $2,236 $2,236 0%

11 SEER $2,357 $2,403 -2%

12 SEER $2,510 $2,613 -4%

13 SEER $2,715 $2,895 -6%

18 SEERa $3,302 $3,700 -11%

a

 Costs based on 15 SEER equipment.

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Markup factor = Revenues

Cost of Sales (D.1)

Revenues = ⋅ Markup Factor Cost of Sales (D.2)

The remaining sections of this report describe the methodology used to derive disaggregated and

incremental markups for the NOPR at the distributor and dealer/contractor levels.

D.2 COMPARISON OF SUPPLEMENTAL ANOPR AND NOPR MARKUP

CALCULATIONS

A key question in calculating the net impact of standard-induced price increases, is how these

price increases are passed along to the consumer as the product proceeds through the distribution

chain. The Supplemental ANOPR analysis used an average aggregate markup for businesses in the

distribution chain. In this markup analysis for the NOPR, we disaggregate the different component

costs of business for distributors and dealers, and estimate how sales prices scale with equipment

costs. 

In the Supplemental ANOPR analysis the markup factor on equipment was calculated from

the gross margin for the industry as follows:

Costs of sale are those costs that are incurred in the manufacture of goods sold and provision of

services. For contractors and distributors, costs of sales are comprised of the equipment purchase

cost as well as the labor, facilities, and materials required to handle and install the equipment. This

does not include costs associated with sales, administration and other indirect expenses (such as

other operating expenses and net profits). The implicit assumption behind the markup equation is

that revenues are always directly proportional to the cost of sales, and that there is no distinction

between labor and equipment costs or any other component of the cost of sales. Rearranging Eqn.

D.1 we obtain:

Unless we are certain that the markup on the equipment does not differ from the cost of labor, for

example, the assumption may not provide an accurate estimate of the markup on equipment alone,

much less the markup applied to an incremental change in the unit cost of equipment, which is the

most appropriate markup to use in the rulemaking analysis.

The main reason that the selling price of a product may not be strictly proportional to the

purchase price of the equipment is that businesses incur a wide variety of costs. Therefore, when the

purchase price of equipment and materials increases, only a fraction of the business expenses

increase, while the remainder of the businesses’ expenses stay relatively constant. For example if

the unit price of an air conditioner increases by 30%, it is unlikely that the cost of secretarial support

in an administrative office will increase by 30% also. Certain business expenses are relatively uncorrelated with the cost of equipment or cost of goods. 

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Revenues Equipment = ⋅ Markup Factor Materials Expense Markup Factor Labor Expense + Labor ⋅ (D.3)

In the analysis for the NOPR analysis we use two independent methods for estimating the

different markups on the cost of equipment only. One method, called the accounting approach, is

an analysis of the disaggregated business financial statements; and the other method, called the

econometric approach, is a statistical analysis of correlation between different business expenses.

These two independent methodologies yield approximately the same result for the estimated markup

on incremental equipment cost increases. Our analyses reproduce the results for the average markup

factor as a special case when simplifying assumptions are made. But the analyses also suggest that

the simplifying assumptions that lead to the Supplemental ANOPR result overestimated the markup

on incremental equipment costs. 

For the accounting approach we analyze the disaggregated business expenses reported by the

relevant business association. Those expenses for payroll, labor, or occupancy, are assumed to scale

with labor expenses, while all other expenses are assumed to scale with aggregate direct costs. This

is a straightforward approach to evaluating disaggregated and marginal markups.

For the econometric approach, we performed a statistical analysis of U.S. Census Bureau data

using a price model that allows an additional degree of freedom more than the model used for the

Supplemental ANOPR. The extra degree of freedom in the econometric model allows part of the

gross profit to scale with labor or payroll expenses while the other part of the gross profit to scale

with purchased materials and equipment costs. The price model in the revised analysis is:

In the econometric approach, we used U.S. Economic Census data from 1997 and tested

which model, (1) the Supplemental ANOPR model, or (2) the model for the NOPR, better explained

state-by-state revenue data for the industry, and if differences between the parameters found in the

NOPR analysis and the Supplemental ANOPR analysis were statistically significant. We determined

that the differences are statistically significant according the assumptions used in the regression

analyses. We also computed the markup factors for the revised model and the confidence intervals

for the markup factors.

We performed several sensitivity tests on our statistical calculations. These sensitivities

included adding an extra parameter in our cost equation to calculate incremental (or marginal)

markup factors. For the contractor industry, we also tested the scaling of gross profit vs. direct labor

(installation labor for dealers) and total payroll. 

D.3 AVERAGE, DISAGGREGATED, AND INCREMENTAL MARKUPS

In this section we discuss the difference between average, disaggregated, and incremental

markups. Different markups arise as they are averaged over different categories of costs, or as they

are averaged over different scales of cost. 

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In the Supplemental ANOPR analysis, the contractor markup is the average markup for all

direct costs, which include both direct labor and materials and equipment. If we divide the direct

costs into different categories and calculate separate markups on the different categories of direct

costs, then we are calculating disaggregated markups. Disaggregated markups can still be average

or incremental, but they are broken down into different categories of costs and are thus

“disaggregated.”

Incremental (or marginal) markups are the markups that are applied to costs at the margin.

That means for an incremental cost increase (e.g., one resulting from a new efficiency standard), it

is the markup factor that is applied to the incremental equipment purchase cost increase to get the

incremental selling price increase. A marginal price increase may be obtained by taking cost and

price data and fitting a line for the cost/price relationship. The slope of the price versus cost line

gives the incremental markup. If the fitted line has an intercept of zero, then the marginal price

equals the average price because in that case the price is strictly proportional to cost. 

Figure D.1 illustrates for wholesalers/distributors the concept of average, disaggregated, and

incremental markups. At the current baseline efficiency level (i.e., 10 SEER), the average markup

covering both equipment and labor expenses is 1.37. As indicated in the analyses described

previously, the incremental markup associated with the incremental change in equipment and

materials cost is approximately 1.09. In our analyses, we have found that the incremental markup

for equipment and materials is not significantly different from the average disaggregated equipment

markup. For each minimum efficiency level beyond the current baseline, the markup on equipment

is composed of two portions; the average markup (1.37) that is applied to the “base” portion (i.e.,

that portion associated with covering expenses of the current baseline equipment) and the marginal

markup (1.09) that is applied to the incremental change in equipment cost (e.g., a change resulting

from new efficiency standards). As a result of applying different markups to the “base” and

“incremental” portions of the equipment cost, the aggregate markup decreases slightly with

increasing efficiency. For example, in the case of split system air conditioners as shown in Table

D.1, the aggregate markups resulting from an average markup of 1.37 on the “base” portion and 1.09

on the “incremental” portion are 1.33 at 11 SEER, 1.30 at 12 SEER, and 1.26 at 13 SEER.

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D-6

Figure D.1 Base and Incremental Costs and Markups for Split System Air

Conditioners at the Wholesaler Level

D.4 ANALYSIS OF FINANCIAL STATEMENTS

The accounting approach we used to estimate marginal disaggregated equipment markups

was based on analysis of income statements from the air conditioning wholesaler and contractor

industries. This method is conceptually straightforward, but since it is based on only a few

companies, may not accurately estimate the markup applied generally across each industry.

Furthermore, we can get only a limited appreciation for the variability associated with the markups

across companies.

D.4.1 Distributors

Table D.I at the end of this appendix shows the detailed cost breakdown for an average airconditioning wholesale business. The cost data is provided by the 1998 Wholesaler Profit Survey

Report published by the Air-conditioning & Refrigeration Wholesalers (ARW).1

 That report showed

(on page 23) that 14.8% of sales revenues is spent on recovering payroll expenses, that 3.6% is spent

on recovering occupancy expenses, that 8.2% of sales revenues goes to other operating expenses

(5.5%) and operating profit (2.7%) which we might expect to scale with the unit price of equipment.

Since the costs of sales is 73.6% of total sales revenues, this indicates that the markup on

incremental equipment costs should be about 1+8.2%/73.6% = 1.11.

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D-7

Markup factor b

m

m m

= + =+ − = − ( ) ( )( )1 1

1

1

1 (D.4)

P PW M bPW out in b = + + =+⋅ + in b ( )( ) 1 (D.5)

D.4.2 Dealers/Contractors

To examine the detailed cost breakdown, or disaggregation of the different components of

the gross margin expenses we analyze data that is provided in the 1995 edition of Financial Analysis

for the HVACR Contracting Industry published by the Air Conditioning Contractors of America.2

The data for the cost breakdown is provided in Table D.II at the end of this appendix. 

In this cost disaggregation we select those costs that would scale with wage rates and those

costs that would tend to scale with all direct costs. This is a method for assigning the gross margin

expenses between those costs that would scale with equipment and miscellaneous expenses, and

those gross margin costs that would tend to scale with direct labor costs. For example in state-bystate comparisons wage rates in different states may vary considerably. The hypothesis of this

analysis approach is that those components of the gross margin that are related to wages will tend

to correlate with the wage portion of the direct costs. If we do this assignment, then we find that

16.43% of total costs are part of the gross margin and would scale with wages, while about 18.4%

of total costs are part of the gross margin and may scale with all direct costs. This implies that the

markup factor for non-wage direct costs would be 1 +18.4%/65.4% = 1.28. Similarly, the markup

factor for direct labor costs should be 1 + 0.28 + 16.4%/19% = 2.15.

D.5 ECONOMETRIC ANALYSIS OF U.S. CENSUS BUREAU DATA

To address some of the limitations associated with basing our markup analysis on a small

sample of company financial reports, we analyzed U.S. Census Bureau data for each industry.

Results of the data analysis agree with the conclusion reached using the financial statements.

Furthermore, the Census Bureau data suggests the range of markup factors could apply.

For purposes of explaining the econometric analysis, equations presented at the beginning

of this appendix are expressed in different terms. The markup factor as presented in Eqn. D.1 is put

in terms of the gross profit margin, or gross margin, as follows:

where (1+b) is the markup factor and m is the gross margin which is the gross profit (M) divided by

total revenues (Pout). Gross profit is defined as total revenues (Pout) minus direct costs. Direct costs

are those costs that are attributed directly to the products and services being sold. Direct costs may

include purchased equipment and materials (Pin) and billable labor (Wb). 

In expressing the markup factor as shown in Eqn. D.4, Eqn. D.2 is expressed as:

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D-8

P b P cW out =+⋅ ++⋅ in () () 1 1 (D.6)

The above equation assumes that the gross profit is directly proportional to the sum of direct costs.

This assumption, which was used in the Supplemental ANOPR, is only approximately true, and in

the markup analysis for the NOPR we examine whether or not relaxing this assumption results in

a significantly different markup factor.

In the markup analysis for the NOPR, we calculated a slightly more complicated price model

that allows one more degree of freedom than the Supplemental ANOPR model (as presented in

general terms in Eqn. D.3). Using the terms defined above in Eqns. D.4 and D.5, Eqn. D.3 becomes:

Where Pin is the purchased materials and equipment costs, and W is a labor cost, either total payroll

(Wt

=Wb+Wo) or billable contractor labor payroll (Wb). Note that there are two types of labor payroll

expenses: one is billable labor which we label with the variable Wb, and labor that is usually included

as part of the gross margin or gross profit (Wo) which we refer to as overhead or operational labor.

The total payroll is the sum of the billable and overhead payroll. The Supplemental ANOPR model

is a special case of the revised analysis where either W = 0, or (1+b) = (1+c), for distributor markup

and dealer markup factors, respectively. 

D.5.1 Distributor Markups

The economic data of revenues and costs for warm air heating and air conditioning

equipment and supplies wholesalers are provided by the U.S. Census Bureau, 1997 Economic

Census (refer to Table D.III at the end of this appendix).3

 For most states the U.S. Census data gives

the value of the total sales, the payroll amounts, and the operating expenses. Given an estimate of

the operating profit (defined as total sales minus the cost of goods sold and all operating expenses),

a value for the gross profit (defined as total sales minus the cost of goods sold) can be calculated

state-by-state. Then, using the variability in the relative size of costs of goods and payroll state-tostate, we develop a regression between the cost of goods, payroll and the gross margin per firm.

To provide a reasonably accurate estimate of the state-by-state average operating profit per

firm, we examined cross-industry wholesale operating profits from the 1992 U.S. Census.4

 This data

shows an average of 5.5% operating profit and a standard deviation of about 2.5%. (Note: In the

1992 U.S. Census data, operating profit is termed gross profit.) We decided to examine a range of

operating profit values to provide a sensitivity check on our average operating profit assumptions.

We used a 3% operating profit as the low end, the 5.5% operating profit assumption as the median

and an 8% operating profit assumption as the high end. The average operating profit for the air

conditioning wholesale industry in 1992 was 5.5%. 

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D-9

M

P b PP c

W

out P

in

out

o

out

=⋅ + + ⋅ ( ) 1 (D.7)

Table D.III at the end of this appendix shows the state-by-state wholesale business data that

is used to dis-aggregate the different components of the wholesale gross margin. Using Microsoft

Excel’s regression tool we calculate b and 1+c in the following equation

where M is the gross profit (Pout - Pin), 1+b is the markup factor on equipment expenses, Pin is the

equipment expense, 1+c is the scaling factor for payroll-related expenses, and Wo is the payroll of

the wholesale business which is all overhead payroll since there is no billable labor in wholesale

distribution.

From the two-dimensional regression we have the following table (Table D.3), where the Min

values represent the low end of the 95% confidence interval and the Max value represents the high

end of the 95% confidence interval.

Table D.3 Distributor Markups derived from Census Data

Operating Profit Assumption

Equipment Markup Factor (1+b) Labor Markup Factor (1+c)

Min Mean Max Min Mean Max

3% of Total Sales 1.02 1.06 1.12 1.29 1.66 2.04

5.5% of Total Sales 1.04 1.09 1.14 1.33 1.71 2.09

8% of Total Sales 1.06 1.12 1.18 1.37 1.76 2.15

This analysis supports a scenario where the markup factor on incremental equipment costs

are significantly lower than the average markup of 1.37 that was used in the Supplemental ANOPR

analysis. We select 1.09 as a markup factor that is large enough to preserve a substantial operating

profit for the wholesale industry, a figure that is in close agreement with the results obtained from

the accounting analysis. 

One question about the methodology applied to the state-by-state data is that the method

assumed no correlation between operating expense fraction and operating profit. A 1998 wholesaler

profit survey report provided by the Air-conditioning & Refrigeration Wholesalers Association

(ARW) has data that indicates there in fact may be an anti-correlation between the gross margin and

operating profit.5

 The question is what may be the sensitivity of the gross margin calculation to such

correlation effects. By examining page 13 in the ARW report, we find that the operating profit

increases from 1.4% to 2.7% when the total operating expenses decreases from 28.4% to 22.1%. 

We can use the relationship of a 1% operating profit change per 6% operating expense change to

provide an anti-correlation relationship between operating profit and operating expenses. When we

assume a 1% per 6% anti-correlation and recalculate the markup factor for cost of goods using this

assumed relation, we obtain a new markup factor of 1.13 with a 95% confidence interval for the

 EE-RM-STD-98-440 COMMENT 312
D-10

M

P b PP

W

out P

in

out

b

out

=⋅ +  (D.8)

regression ranging from 1.08 to 1.17. To do the calculation, we calculated the deviation of the

fractional operating cost from the mean, and then assumed a 1% change in fractional operating profit

for each 6% change in fractional operating cost. 

D.5.2 Dealer Markups

For the dealer markups a very similar approach was taken. State-by-state data on the HVAC

contractor industry was obtained from the 1997 Economic Census (refer to Table D.IV at the end

of this appendix).6

 We then took the fractional gross margin and examined the two-parameter

regression between the fractional materials cost and factional wage expenses. We did two fits, one

looked at only construction wages as an explanatory variable, while the other looked at total payroll

(similar to the analysis for the wholesale industry). Results are summarized in Table D.4. We find

that when we separate the portions of the gross markup factor according to materials and

construction labor, that the mean markup factor for the materials portion is 1.27, a figure that is in

close agreement with the results obtained from the accounting analysis. We also find that if we

assume that administrative and non-production labor expenses to be constant, then the mean markup

factor on materials and equipment expenses is 1.15. A mathematically equivalent regression can be

done by simply correlating the net value of construction per firm against materials expenses and the

relevant payroll expense. 

Table D.4 Contractor Markups derived from Census Data

Analysis Method

Equipment Markup Factor Labor Markup Factor

Min Mean Max Min Mean Max

2D Regression: W=construction worker wages 1.09 1.27 1.45 1.66 1.99 2.33

2D Regression: W=all employees payroll 0.99 1.15 1.31 1.38 1.58 1.79

Note that when we use this state-by-state data to calculate the following model:

We obtain an average markup factor of 1.52, which agrees closely with the markup factor used in

the Supplemental ANOPR analysis. Our approach therefore starts with a price model consistent with

the Supplemental ANOPR analysis, and then removes some of the assumptions that restrict the

description of the scaling behavior of the gross margin. When the assumption of equality between

equipment and labor cost markups is removed, we find a significant difference between the two

markup factors. The statistical confidence tests done with the slightly less restrictive model show

that the assumptions behind the presumed mathematical restrictions in the Supplemental ANOPR

analysis are not supported by the U.S. Economic Census data. 

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D-11

P b P cW a

M b P cW a

out in

in

=+⋅ ++⋅+

=⋅ +⋅ +

() () 1 1

(D.9)

D.6 SENSITIVITY TEST OF MARGINAL MARKUP MEASUREMENTS

As a further sensitivity test for our dis-aggregated markup numbers, we re-calculate the

materials and equipment markups using a three parameter model that allows the marginal markup

on equipment to be different than the average dis-aggregated markup on materials. In this slightly

more complicated model the output cost of materials is a three-parameter linear function of

equipment and labor costs, specifically:

In this revenue model Pin is the per-firm annual cost of materials and equipment, (1+b) is the

marginal markup factor on materials and equipment, M is the gross profit for dealers and it is the

gross profit minus the payroll for distributors, and Pout is the total per firm revenues. Also, W is

either the total payroll (Wt, for wholesale business) or the payroll of construction worker labor (Wb,

for dealers). 

When we calculate the parameters for this three-parameter per-firm revenue model using

state-by-state averages from Census data we obtain:

Table D.5 Contractor and Distributor Marginal Markups derived from Census Data

Industry Type

Equipment Markup Labor Markup Constant ($1000/firm)

Min Mean Max Min Mean Max Min Mean Max

Contractor 0.97 1.17 1.37 1.71 2.02 2.32 -3 31 65

Distributor 1.04 1.09 1.14 1.08 1.54 2.00 -41 60 160

These results show that the constant term in the per-firm revenue model is statistically close to zero

(i.e. zero is included in the 95% confidence interval for the constant). Also, the marginal equipment

markup factors for the marginal markup analysis substantially overlap with the markup factors for

the average dis-aggregated markups obtained from the two-parameter price model. 

D.7 SUMMARY OF RESULTS

Table D.6 summarizes the results from our analyses. We find that there is a range of possible

markup values that are obtained, but that the mean recomputed markup factors range from 1.06 to

1.13 for the distributor markup on equipment price and from 1.15 to 1.28 for the contractor

equipment markup. 

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Table D.6 Price Markup Comparisons

Analysis Method

Equipment

Markup

Wage

Markup

Dealer Markups

ACCA Data Analysis allocating Gross Margin Payroll expenses to install labor 1.28 2.15

Correlation Analysis: installation labor constant 1.27 1.99

Correlation Analysis: all labor constant 1.15 1.58

Correlation Analysis: marginal markup (equip. & install. labor ) 1.17 2.01

Distributor Markups

ARW Data Analysis 1.11 -

Correlation Analysis: operating profit fixed @ 3% 1.06 1.66

Correlation Analysis: operating profit fixed @ 5.5% 1.09 1.71

Correlation Analysis: operating profit fixed @ 8% 1.12 1.76

Correlation Analysis: operating profit and operating expenses anti-correlated 1.13 1.45

Correlation Analysis: marginal markup 1.09 2.00

For the dealer markups, we calculate the markup from a disaggregated accounting of dealer

costs obtained from the Financial Analysis For The HVACR Contracting Industry (refer to Table

D.II). In addition, three correlation analyses were performed: The first analysis divides the costs into

one component that scales with direct labor (i.e. installation labor) and another that scales with

equipment costs. The second analysis divides costs into a component that scales with equipment and

another part that scales with total payroll. And the third analysis allows firms to have one cost

component that scales with neither installation labor nor equipment, one component that scales with

installation labor, and a third component that scales with equipment. We refer to the third approach

as a marginal markup calculation (because is calculates the markup scaling at the margin, for

incremental changes in firm expenses). 

For distributor markups, we calculate the markup from a disaggregated accounting of

distributor costs obtained from the 1998 Wholesaler PROFIT Survey Report by the Air-conditioning

& Refrigeration Wholesalers Association (ARW) (refer Table D.I). This results in an estimate of

1.11 for the distributor markup. In addition, five correlation analyses are performed. The first four

analyses test different sensitivities regarding our assumption about operating profits. The available

data did not directly report cost of goods, so the cost of goods was calculated using different

assumptions about the operating profit (total sales minus all costs). The first three analyses assumed

that the operating profit is a fixed amount of total sales, while the fourth analysis assumed that there

exists an anti-correlation between operating profit and operating expenses. The fifth correlation

analysis examines marginal markups (with a fixed 5.5% operating profit assumption) where a

component of per-firm business expenses is allowed to scale with neither payroll nor cost of goods.

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D-13

1.00

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

SANOPR Marginal ARW Data 3% Profit 5.5% Profit 8% Profit Anti-Corr.

Sens.

Analysis Method

Markup

Figure D.2 Comparison of Wholesaler/Distributor Markups

In addition to summarizing the result in the previous table we plot the different

methodologies, their answers and the approximate error bars (95% confidence interval) for the

different markup analysis methods and assumptions.

Figure D.2 shows the results for the distributor markup calculations. We see from the

‘Wholesale Equipment Markups’ figure that once we depart from the average markup assumption,

different methods produce values between 1.02 to 1.18. We select a value of 1.11 for the distributor

markup based on the disaggregated accounting of distributor costs from the ARW data.

Contractor markups on equipment calculated from different approaches are shown in Figure

D.3. Most methods provide results that are significantly lower than the 1.55 average markup used

in the Supplemental ANOPR analysis. We adopt the analysis with the constant install labor as a

reasonable approach consistent with our analysis of the ACCA disaggregated accounting of gross

margin expenses. 

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D-14

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

SANOPR Marginal ACCA Data Install Labor

Const.

All Labor Const.

Analysis Method

Markup

Figure D.3 Comparison of Dealer/Contractor Markups

D.8 CONCLUSION

We have performed a thorough analysis of the markup on incremental equipment costs for

distributors and dealers of air conditioners and heat pumps. Analysis of company financial

statements provides strong evidence that the average aggregate markups used in the Supplemental

ANOPR analysis over-estimate the markups on incremental equipment costs. Preliminary statistical

analysis of Census data seems to support that conclusion and yield similar markup estimates. The

statistical analysis also provides additional insight into the distribution of markups. Given the weight

of evidence and the range of results, we select 1.09 as a reasonable estimate of the distributor markup

on incremental costs and will continue to use 1.37 as the distributor markup on the base portion of

equipment cost. For the dealer, we select 1.27 as a good estimate for the dealer markup on both the

incremental and base portions of equipment costs, and we raise the installation labor price to

compensate for the drop in average equipment markup. 

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Table D.I Disaggregated Costs for ARW Wholesalers/Distributors

Taken from the 1998 Wholesaler Profit Survey Report published by the Air-conditioning &

Refrigeration Wholesalers Association ARW). Note that some figures may not add up due to

rounding.

Item Fraction Scaling

Cost of Goods Sold 73.6%

Gross Margin 26.4%

Payroll Expenses

Executive Salaries & Bonuses 2.7% Labor

Inside Sales Salaries/Wages 3.2% Labor

Outside Sales Salaries/Commissions 2.2% Labor

Warehouse & Delivery Salaries/Wages 2.3% Labor

All Other Salaries/Wages & Bonuses 2.1% Labor

Payroll Taxes 1.1% Labor

Group Insurance 0.7% Labor

Benefit Plans 0.5% Labor

Total Payroll Expenses 14.8%

Occupancy Expenses

Utilities: Heat, Light, Power, Water 0.4% Labor

Telephone 0.6% Labor

Building Repairs & Maintenance 0.2% Labor

Rent or Ownership in Real Estate 2.4% Labor

Total Occupancy Expenses 3.6%

Other Operating Expenses

Advertising and Promotion 0.9% All Costs

Insurance 0.4% All Costs

Depreciation 0.7% All Costs

Bad Debt Losses 0.3% All Costs

All Other Operating Expenses 3.2% All Costs

Total Other Operating Expenses 5.4%

Operating Profit 2.7% All Costs

Gross Margin Scaling with All Costs 8.2%

Gross Margin Scaling with Labor Only 18.4%

Average Markup Factor 1.36

Markup Factor for Non-Labor Costs 1.11

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Table D.II Disaggregated Costs for HVACR Contractors

From the 1995 edition of Financial Analysis for the HVACR Contracting Industry published by the

Air Conditioning Contractors of America (ACCA).

Item Fraction Scaling

Direct Materials 22.70%

Equipment Installed 14.22%

Direct Labor 19.01%

Direct Subcontract 5.55%

Direct Other 3.97%

Total Cost of Sales 65.45%

Gross Margin 34.55%

Operating Expenses

Advertising 1.10% All Costs

Bad Debts 0.16% All Costs

Depreciation 1.02% All Costs

Interest Expenses 0.33% All Costs

Liability Insurance 1.12% All Costs

Other Insurance 1.36% All Costs

Occupancy Costs 1.24% Labor

Payroll Taxes/Fringe Benefits 4.02% Labor

Selling Expense 1.49% All Costs

Officer Salaries 3.80% Labor

Sales and Estimating Salaries 2.69% Labor

Administration Salaries 3.18% Labor

Warehouse Salaries 0.46% Labor

Unapplied Labor 1.04% Labor

Vehicle/Maintenance Repairs 1.82% All Costs

Other Operating Expenses 5.13% All Costs

Total Operating Expenses 29.96%

Net Operating Profit 4.59% All Costs

Other Income 0.79% All Costs

Other Expenses -0.49% All Costs

Net Profit Before Income Taxes 4.89%

Gross Margin Scaling with all Costs 18.42%

Gross Margin Scaling with Labor Only 16.43%

Average Markup Factor 1.53

Markup Factor for Non-Labor Costs 1.28

Markup Factor for Labor Costs 2.15

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Table D.III U.S. Census Data for Air-Conditioning Wholesalers/Distributors

Data from U.S. Census Bureau, 1997 Economic Census, Wholesale Trade, Geographic Area Series

(NAICS code 42173). All values in the table below are taken from Table 1 of the Census report.

Operating profit numbers are calculated with fixed percentage profit assumption.

Number of Total Sales Payroll Operating Exp. Operating Profit (thousands)

State firms thousands thousands thousands 3% 5.5% 8%

Alabama 123 $334,554 $27,473 $54,156 $10,037 $18,400 $26,764

Connecticut 58 $204,159 $28,127 $46,483 $6,125 $11,229 $16,333

Florida 445 $1,226,541 $130,367 $244,635 $36,796 $67,460 $98,123

Idaho 31 $64,013 $6,201 $12,317 $1,920 $3,521 $5,121

California 374 $1,418,645 $148,279 $273,028 $42,559 $78,025 $113,492

Louisiana 123 $187,972 $29,924 $59,059 $5,639 $10,338 $15,038

Maryland 114 $469,325 $43,287 $79,097 $14,080 $25,813 $37,546

Michigan 188 $640,856 $69,630 $131,499 $19,226 $35,247 $51,268

New Jersey 181 $586,349 $77,995 $143,024 $17,590 $32,249 $46,908

New York 270 $918,325 $111,921 $206,395 $27,550 $50,508 $73,466

Oregon 54 $366,449 $25,083 $44,120 $10,993 $20,155 $29,316

Texas 521 $2,722,527 $209,839 $592,747 $81,676 $149,739 $217,802

Wisconsin 106 $357,000 $45,111 $73,302 $10,710 $19,635 $28,560

Arizona 81 $361,629 $38,771 $63,032 $10,849 $19,890 $28,930

Colorado 76 $234,628 $28,625 $51,912 $7,039 $12,905 $18,770

Indiana 139 $510,718 $51,994 $96,568 $15,322 $28,089 $40,857

Missouri 135 $806,101 $51,976 $96,259 $24,183 $44,336 $64,488

Nebraska 44 $113,047 $11,603 $23,195 $3,391 $6,218 $9,044

South Carolina 111 $318,191 $28,280 $50,262 $9,546 $17,501 $25,455

North Dakota 6 $5,625 $736 $994 $169 $309 $450

Tennessee 150 $821,211 $72,885 $124,843 $24,636 $45,167 $65,697

Washington 105 $361,962 $41,547 $76,915 $10,859 $19,908 $28,957

Minnesota 75 $349,361 $40,805 $69,926 $10,481 $19,215 $27,949

Kentucky 99 $411,191 $35,996 $72,273 $12,336 $22,616 $32,895

Arkansas 56 $121,159 $12,112 $26,020 $3,635 $6,664 $9,693

Delaware 25 $61,435 $6,278 $10,077 $1,843 $3,379 $4,915

Georgia 206 $724,408 $68,794 $129,235 $21,732 $39,842 $57,953

Hawaii 13 $35,290 $3,595 $7,848 $1,059 $1,941 $2,823

Illinois 237 $902,720 $86,711 $181,192 $27,082 $49,650 $72,218

Iowa 41 $59,672 $7,486 $14,234 $1,790 $3,282 $4,774

Mississippi 49 $101,853 $8,672 $18,449 $3,056 $5,602 $8,148

Montana 16 $28,924 $3,688 $6,719 $868 $1,591 $2,314

Nevada 39 $149,749 $12,654 $23,734 $4,492 $8,236 $11,980

New Mexico 23 $65,773 $6,558 $14,473 $1,973 $3,618 $5,262

North Carolina 226 $762,218 $77,307 $142,805 $22,867 $41,922 $60,977

Ohio 236 $845,271 $94,170 $171,236 $25,358 $46,490 $67,622

Oklahoma 89 $221,039 $19,873 $37,626 $6,631 $12,157 $17,683

Pennsylvania 235 $756,528 $86,397 $89,554 $22,696 $41,609 $60,522

Utah 38 $138,458 $14,866 $24,734 $4,154 $7,615 $11,077

Virginia 141 $533,211 $52,658 $101,976 $15,996 $29,327 $42,657

West Virginia 106 $81,211 $6,656 $13,503 $2,436 $4,467 $6,497

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Table D.IV U.S. Census Data for HVAC Contractors

Data from U.S. Census Bureau, 1997 Economic Census, Plumbing, Heating, & Air-Conditioning Contractors (NAICS

code: 235110, SIC code: 171100). All monetary values are in dollars per firm. The Number of Firms are provided in

Table 11 of the Census Report (column B (establishments located in the state) plus column F (establishments not

reporting)). The Net Value and Materials are provided in Table 3 of the Census Report, columns B and D, respectively.

The Construction Payroll and Total Payroll are provided in Table 2 of the Census Report, columns I and H, respectively.

State

Number

of firms

Net Value

 per firm

Materials

per firm

Construction

Payroll per firm

Total Payroll

 per firm

Alabama 1413 $817,573 $332,335 $185,157 $265,764

Alaska 187 $878,198 $332,160 $208,893 $296,770

Arizona 1344 $1,081,209 $498,973 $234,172 $330,664

Arkansas 980 $559,841 $238,308 $125,924 $172,609

California 6776 $1,096,027 $453,715 $270,016 $369,007

Colorado 1654 $925,321 $411,807 $217,824 $301,684

Connecticut 1254 $727,402 $290,203 $168,619 $242,767

Delaware 288 $1,308,066 $477,521 $338,219 $484,049

Florida 4803 $808,400 $362,941 $168,369 $251,964

Georgia 2589 $958,351 $412,534 $196,896 $287,993

Hawaii 243 $950,984 $347,305 $221,103 $324,564

Idaho 546 $847,046 $371,817 $182,502 $246,954

Illinois 3756 $1,130,302 $429,262 $295,798 $398,058

Indiana 1973 $1,098,435 $446,279 $279,622 $382,440

Iowa 938 $908,019 $355,371 $214,907 $293,711

Kansas 1065 $847,007 $388,001 $187,319 $259,248

Kentucky 1178 $847,152 $356,896 $197,961 $269,195

Louisiana 1200 $757,721 $325,003 $157,684 $231,641

Maine 552 $451,821 $198,065 $99,317 $142,630

Maryland 2037 $1,116,541 $489,080 $254,578 $374,130

Massachusetts 2172 $848,455 $363,227 $186,431 $267,121

Michigan 3187 $928,415 $366,709 $221,138 $307,104

Minnesota 1416 $1,100,958 $455,536 $265,766 $369,213

Mississippi 746 $702,544 $330,367 $139,425 $195,009

Missouri 1824 $892,012 $345,791 $225,493 $312,252

Montana 412 $553,058 $269,126 $124,284 $165,854

North Dakota 248 $827,331 $340,887 $210,633 $272,327

North Carolina 3057 $899,984 $387,419 $198,937 $286,183

Nebraska 662 $801,965 $344,559 $190,705 $264,314

Nevada 515 $1,575,707 $691,083 $378,497 $496,474

New Hampshire 462 $691,561 $303,656 $148,652 $207,582

New Jersey 3320 $741,231 $299,900 $174,226 $247,283

New Mexico 600 $596,717 $259,115 $156,492 $206,905

New York 5234 $884,105 $360,541 $193,445 $291,500

Ohio 3329 $1,010,347 $405,283 $252,854 $347,859

Oklahoma 1156 $586,724 $252,590 $116,183 $161,541

Oregon 1079 $1,112,995 $461,787 $308,114 $407,706

Pennsylvania 3546 $1,006,816 $418,842 $234,297 $329,217

Rhode Island 356 $573,893 $256,272 $123,124 $176,003

S Dakota 311 $502,113 $230,621 $109,987 $160,559

South Carolina 1351 $799,229 $358,672 $194,019 $265,561

Tennessee 1612 $1,087,848 $506,068 $235,924 $352,965

Texas 5516 $982,148 $449,987 $207,952 $298,124

Utah 835 $939,435 $375,856 $207,865 $280,911

Virginia 2391 $822,614 $361,340 $198,761 $281,273

Vermont 245 $563,273 $224,543 $137,878 $184,453

Washington 1746 $1,008,192 $397,266 $239,093 $340,587

West Virginia 496 $589,083 $279,732 $133,143 $169,135

Wisconsin 1981 $979,285 $373,594 $258,869 $352,044

Wyoming 264 $445,027 $199,686 $98,580 $148,114

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1. Air-conditioning & Refrigeration Wholesalers Association (ARW), 1998 Wholesaler

PROFIT Survey Report, Based on 1997 Wholesaler Operations, 1998. Boca Raton, FL. 

<http://www.arw.org>

2. Air Conditioning Contractors of America (ACCA), Financial analysis for the HVACR

Contracting Industry, 1995 Edition, 1995. Washington, DC.

3. U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census

Bureau, 1997 Economic Census, Wholesale Trade, Geographic Area Series, March-April,

2000. Washington, DC. Report No. EC97W42A-XX(RV). (Note: There are a total 51

reports; thus, the XX in the report number refers to one of the 50 U.S. states or the District

of Columbia.) <http://census.gov/epcd/www/97EC42.HTM>

4. U.S. Department of Commerce, Economics and Statistics Administration, Bureau of the

Census, 1992 Census of the Wholesale Trade, Subject Series, Miscellaneous Subjects,

November, 1995. Washington, DC. Report No. WC92-S-4. Table 9. 

<http://www.census.gov/prod/2/bus/whsle/wc92-s-4.pdf>

5. Air-conditioning & Refrigeration Wholesalers Association (ARW), 1998 Wholesaler

PROFIT Survey Report, Based on 1997 Wholesaler Operations, 1998. Boca Raton, FL. 

<http://www.arw.org>

6. U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census

Bureau, Plumbing, Heating, and Air-Conditioning Contractors, 1997 Economic Census,

Construction, Industry Series, July, 1999. Washington, DC. Report No. EC97C-2351A.

<http://www.census.gov/prod/ec97/97c2351a.pdf>

REFERENCES

 EE-RM-STD-98-440 COMMENT 312