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 incrementalmarkup 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 add ition, 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 incrementalmarkups 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.D-2 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 Conditioners a $1,279 / $1,367 $1,190 Heat Pumps a $2,280 / $2,160 $2,035 Builder Markup 1.09 b 1.00 c Sales Tax 1.04 b 1.07 d 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 repl acement 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 SEER a $3,302 $3,700 -11%

aCosts based on 15 SEER equipment.D-3 

### 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 supportin an administrative office will increase by 30% also. Certain business expenses are relatively uncorrelated with the cost of equipment or cost of goods.D-4 Revenues Equipment + Labor =⋅ ⋅ Markup Factor Materials Expense Markup Factor Labor Expense (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.D-5 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.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.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, andthose 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 ( P out ). Gross profit is defined as total revenues (P out ) 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 ( P in ) and billable labor ( W b ).
In expressing the markup factor as shown in Eqn. D.4, Eqn. D.2 is expressed as: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:

WhereP inis the purchased materials and equipment costs, and W is a labor cost, either total payroll ( W t =W b +W o ) or billable contractor labor payroll ( W b ). Note that there are two types of labor payroll expenses: one is billable labor which we label with the variable W b , and labor that is usually included as part of the gross margin or gross profit ( W o ) 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 calculatedstate-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. 4This 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%.D-9 

### M P b P P c W P out 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+cin the following equation

whereM is the gross profit ( P out - P in ), 1+b is the markup factor on equipment expenses, P in is the equipment expense, 1+c is the scaling factor for payroll-related expenses, andW o 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 theD-10 

### M P b P P W P out 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.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 P in 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 P out is the total per firm revenues. Also, W is either the total payroll ( W t , for wholesale business) or the payroll of construction worker labor ( W b , 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.D-12 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.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 MethodMarkup

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.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 MethodMarkup

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.D-15 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 1.11D-16 Table D.II Disaggregated Costs for HVACR Contractors

From the 1995 edition of Financial Analysis for the HVACR Contracting Industrypublished 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 2.15D-17 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 $6,497D-18 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 $148,114D-19 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