Report to the Record

Costs and Economic Impact 

Analysis for Alaska Seafood 

Processors (Facilities and 

Firms)

U.S. Environmental Protection Agency

Office of Water (4303T)

1200 Pennsylvania Ave., NW

Washington, DC 20460

August 2013
Cost and Economic Impact Analysis for Alaska Seafood Processors

ii

Table of Contents

1. Introduction and Summary of Key Results....................................................................... 1

1.1 Summary: Petitioning Locations...................................................................................... 2

1.2 Summary: Non-Petitioning Additional Locations of Interest (Kenai Peninsula and 

Sitka)................................................................................................................................ 2

2. Costs and Impacts to Facilities and Firms in the Petitioning Locations......................... 3

2.1 Annualized Costs to Facilities in the Petitioning Locations ............................................ 3

2.2 Financial Impacts on Facilities in the Petitioning Locations ........................................... 6

2.2.1 Baseline Analysis...................................................................................................... 6

2.2.2 Post-Compliance Analysis........................................................................................ 6

2.3 Impacts on Firms Owning Facilities in the Petitioning Locations................................... 7

2.3.1 Impacts on All Firms ................................................................................................ 7

2.3.2 Impacts on Small vs. Large Firms ............................................................................ 9

3. Costs and Impacts to Facilities and Firms in the Non-Petitioning Locations of Interest

............................................................................................................................................... 9

3.1 Annualized Costs to Facilities in the Locations of Interest............................................ 10

3.2 Financial Impacts on Facilities and Firms in the Locations of Interest ......................... 11

4. Additional Analyses........................................................................................................... 11

4.1 Barriers to Entry............................................................................................................. 11

4.2 Alternative Method for Assessing Adequate Cash Flow for Capital Replacement Needs

........................................................................................................................................ 12

5. References........................................................................................................................... 13

Appendix A Methodologies Used to Analyze Costs and Impacts on Seafood Processing 

Firms and Facilities ........................................................................................................... 14
Cost and Economic Impact Analysis for Alaska Seafood Processors

iii

List of Tables

Table 1. Summary of Results for Processing Locations Included in Petition ................................ 4

Table 2. Petitioning Locations: Aggregate Annualized Pre-Tax Facility Costs for Scenarios 1 and 

2b using Survey Reported Discount Rates and OMB's Recommended 7 Percent Discount Rate 

($2010, thousands).......................................................................................................................... 5

Table 3. Summary of Results for Additional Non-Petitioning Processing Locations.................. 10
Cost and Economic Impact Analysis for Alaska Seafood Processors

1

1. Introduction and Summary of Key Results

This report presents the annualized costs, including costs per pound of waste removed, and economic 

impact analyses, for direct discharging Alaska Seafood Processing Industry firms and facilities associated 

with the petitioning locations of Cordova, Juneau, Ketchikan, and Petersburg to meet the effluent 

limitations guidelines (ELGs) as promulgated for non-remote locations. No direct dischargers are 

currently located in Anchorage, another original petitioning location (46 FR 2544; January 9, 1981). EPA 

conducted its analysis of two scenarios: Scenario 1, screening and discharge of resulting wastewater and 

offshore disposal of screened solids, and Scenario 2b, screening and discharge of resulting wastewater 

and cooperative by-product recovery of screened solids. SeeReport of Quality Activities Supporting 

Alaska Seafood Processing Cost Estimates (EPA 2013b). Only Scenario 1 is considered a basis for the 

regulatory requirements. Scenario 2b is discussed as a discretionary solids management alternative that 

EPA would like to encourage. 

This report also presents similar cost and impact data on firms and facilities located in the Kenai

Peninsula and Sitka processing locations, currently classified as remote. EPA is considering reclassifying 

these locations and Dutch Harbor as non-remote.1 Costs and impacts for Dutch Harbor are not included in 

this analysis because all existing facilities in Dutch Harbor that have operated consistently over the long 

term have installed screening technology as well as individual by-product recovery and already comply 

with the non-remote ELGs as promulgated. Therefore, no additional costs would be incurred by these 

three facilities. 

Much of the data underlying the economic impact analysis has been claimed to be Confidential Business 

Information (CBI). Therefore, the discussions below present only aggregated results primarily by 

processing location, and thus are abbreviated from those contained in the CBI version of this report (U.S. 

EPA, 2011a).

Throughout this report, EPA refers to surveyed and modeled facilities or firms. Surveyed facilities/firms 

are those for which EPA sent requests for information by way of a survey questionnaire under Section 

308 of the Clean Water Act. These include nine firms operating seafood processing facilities in Alaska. 

These firms operate nearly all of the processing facilities in the petition locations as well as facilities in 

other locations. Modeled facilities and firms are those that EPA did not survey and that resemble other 

surveyed facilities and firms (e.g., size based on total production, species of fish processed, similarity of 

corporation structure).

The report begins in Section 1 with a summary of key results. Section 2 presents the costs and impacts to 

facilities and firms in the petitioning locations, while Section 3 presents costs and impacts to facilities and 

firms in the non-petitioning remote additional locations of interest, the Kenai Peninsula and Sitka, 

assuming they were to be reclassified as non-remote. Section 4 provides some additional analyses, 

including an assessment of the barriers to entry for new sources, and an alternative analysis for assessing 

adequate cash flow for capital replacement. The methodologies used for these analyses are briefly 

discussed in the main body of this report. Appendix A presents these methodologies in greater detail.

See also Report of Cost Quality Activities Supporting Alaska Seafood Processing Cost Estimates, 

(EPA 2013b) regarding quality assurance, and supporting details and assumptions for costs and economic 

impact analysis.

 1

 The Kenai Peninsula and Seward are considered one processing location for the purposes of this analysis. Sitka is 

a separate processing location.
Cost and Economic Impact Analysis for Alaska Seafood Processors

2

1.1 Summary: Petitioning Locations

The petitioning location firms and facilities located in Cordova, Juneau, Ketchikan, and Petersburg are a

main focus of this report. The following summarizes the key results of the analyses for the locations 

included in the petition:

1. Total annualized costs for all facilities in petitioning processing locations is less than $0.75 

million under Scenario1. 

2. No firms in the petitioning locations are expected to fail regardless of scenario. Small firms are 

not disproportionately affected by the costs. 

3. Given that the costs for Scenario 1 on a facility basis are $0.02 to $0.04 per pound removed. 

These costs in light of the reductions achieved are very low compared to most other industry 

categories for which EPA has promulgated ELGs and are reasonable.

4. The facilities in the petitioning locations can afford the non-remote promulgated ELGs under 

Scenario 1 (based on screening and offshore disposal). The after-tax effects of the costs to meet 

these requirements on cash flow are very low. 

5. Because no impacts to existing facilities are shown in this analysis and because EPA estimates 

the capital cost to new facilities to be a small fraction of engineering contingencies usually 

planned for new facility construction, EPA considers the barriers to entry for new facilities in the 

locations analyzed to be negligible, incremental to any existing barriers to entry.

6. Given that no facilities or firms quantitatively analyzed are estimated to experience financial 

difficulties as a result of meeting non-remote requirements, EPA finds that the small number of 

facilities and firms that were not analyzed quantitatively also could meet the non-remote 

requirements without undue hardship.

1.2 Summary: Non-Petitioning Additional Locations of Interest (Kenai

Peninsula and Sitka)

EPA estimates that the impacts on the firms and facilities in the non-petitioning locations, Kenai

Peninsula and Sitka, should they be reclassified as non-remote, would be similar to those on the 

petitioning location firms and facilities. 

1. Total annualized costs for all facilities in additional processing locations of interest are less than 

$0.9 million.

2. The facilities in these additional locations can afford the non-remote promulgated ELGs under 

Scenario 1 (based on screening and offshore disposal). The after-tax effects of the costs to meet 

these requirements on cash flow are minimal in nearly all cases.

3. Costs for Scenario 1 for the additional locations on a facility basis are slightly higher than for the 

petition facilities, $0.04 to $0.07 per pound removed. These costs in light of the reductions

achieved are very low compared to most other industry categories for which EPA has 

promulgated ELGs and are reasonable. 

4. Because no impacts to existing facilities are shown in this analysis and because EPA estimates 

the capital cost to new facilities to be a small fraction of engineering contingencies usually 

planned for construction, EPA considers the barriers to entry for new facilities in the locations 

analyzed to be negligible, incremental to any existing barriers to entry.

5. Given that no facilities or firms quantitatively analyzed (in these or the petition locations) are 

estimated to experience financial difficulties as a result of meeting non-remote requirements, 

EPA finds that the facilities and firms that were not analyzed quantitatively also could meet the 

non-remote requirements without undue hardship. 
Cost and Economic Impact Analysis for Alaska Seafood Processors

3

2. Costs and Impacts to Facilities and Firms in the Petitioning 

Locations

Section 2 discusses the annualized costs to the surveyed and modeled facilities in the petitioning locations 

and provides the total costs to all facilities in the petitioning locations (Section 2.1). Section 2.2 discusses

the impact these costs potentially may have on those facilities and determines whether any facilities might 

be forced to close if they are required to meet the non-remote BPT effluent limitations as promulgated.

Section 2.3 concludes with the impacts on the owner firms of those facilities. Costs for multiple facilities 

are aggregated to multi-facility firms, and all firms are then analyzed to determine whether the costs of 

these requirements could contribute to potential firm failure. Appendix A describes the methodologies 

used in the analyses discussed below in detail.

2.1 Annualized Costs to Facilities in the Petitioning Locations

This section presents the annualized costs for the petitioning locations in 2010 dollars.2 EPA identified a 

total of 14 facilities operating in these petition cities. Three of these facilities were not surveyed, but EPA 

was able to analyze two of them qualitatively because they have similar characteristics to a surveyed 

facility in their location. See also discussion at section 2.2.2 of this report.

EPA used data in its analyses from responses to the questionnaire and from site visits, augmented with 

publicly available information where appropriate3

. For the small number of facilities for which it had no 

questionnaire responses or other usable data, EPA modeled the potential impacts using information for 

similar processing facilities for which it had questionnaire responses. EPA concluded this approach is 

reasonable because the selected questionnaire facilities resemble the facilities being modeled (e.g., size 

based on total production, species of fish processed, similarity of corporation size). For the modeled 

facilities, EPA extrapolated the impact analysis results to assess qualitatively potential impacts for the few 

non-surveyed facilities and firms in these four processing locations. EPA also used the same approach to 

analyze qualitatively the impacts on facilities in two of the three additional locations it is considering for 

inclusion as non-remote; specifically the Kenai Peninsula and Sitka. Where EPA had a questionnaire 

response for a facility, it used that data. Where EPA did not have a questionnaire response, it modeled the 

impacts based on results from a similar facility for which EPA received questionnaire responses. 

EPA presents aggregate total annualized costs as ranges by processing location in order to prevent 

indirect disclosure of information and data claimed to be Confidential Business Information (CBI). This is 

necessary because many processors have claimed as CBI essential components of these analyses, notably 

financial data. Moreover, in most processing locations there are very few processors and thus CBI may be 

deduced and revealed indirectly. Therefore, much of the detailed cost data developed by EPA for 

individual processors are protected as CBI. These aggregate costs presented as ranges by processing 

location are abbreviated from those contained in the CBI version of this report (U.S. EPA, 2011a).

EPA developed estimates of the incremental effluent reduction benefits (pounds of pollutants removed) 

for screening versus grinding. Typically, EPA estimates the discharges of pollutants at baseline (in this 

 2

 Cash flows are in 2009 dollars; however, these are not greatly different from the 2010 dollars used for costs, and 

are represented here as 2010 dollars. Had these cash flows been inflated to 2010 values, cash flows would be higher 

and percentages of costs to cash flow would have been very slightly smaller.

3 EPA has not attempted to correlate these results with any of the original Petitioners' facilities because some have 

been acquired by other companies or have been closed, and those remaining are likely to be significantly different 

than they were more than 30 years ago.
Cost and Economic Impact Analysis for Alaska Seafood Processors

4

case, grinding) and compares them to discharges assuming the technology basis is installed (in this case 

screening). EPA could not use its standard approach for developing reductions in TSS and oil and grease 

because it does not have baseline information on TSS and oil and grease discharges. Facilities that 

employ grinding do not monitor for TSS and oil and grease for raw untreated wastewaters. Rather, they 

collect data on the mass of incoming raw product and the mass of the final product. As a result, for this 

analysis and in the analysis supporting EPA’s 1981 proposed petition response, EPA used total waste 

generated (i.e., difference between the mass of incoming product minus the mass of the final product) as a 

proxy for the pounds of pollutants removed that would no longer be discharged in the facility effluent 

with the addition of screening. This is appropriate because, as indicated above, total waste generated is 

regularly reported utilizing mass balance data derived from other data regularly collected by processors

for weights of incoming raw product and final products. Moreover, available mass balance data also show 

that facilities using screening technology and by-product recovery achieve waste removals in excess of 90 

percent.

EPA estimated total loads of waste generated for individual processing facilities using data provided by 

processors in NPDES permit annual reports and reported in questionnaire responses. Processors report 

tons of waste generated by subtracting the tons of final product from the tons of raw product. Raw and 

final product weight data are extensive and reliable. Raw product weights are derived from carefully 

weighed incoming fish landings, which serve as the basis for paying fishermen for their catch. These fish 

landing weights are also reported to Alaska state agencies to determine state taxes. Final products are 

weighed carefully for packaging and related purposes.

Table 1 presents a summary of results discussed above for petitioning processing locations.

Table 1. Summary of Results for Processing Locations Included in Petition1

Location

Number 

of Plants 

2

Total 

Annualized Cost 

per Plant -

million $

Removals per 

plant - lbs/yr 3 

(millions)

$/lb removed Economic 

Impact 4

Anchorage 0

< 0.10 1 - 12 0.02 - 0.04

N/A

Cordova 4 No

Juneau 2 No

Ketchikan 5 No

Petersburg 3 No

Total - all 

Plants

14 <$0.75 <30 $0.03 -

1 - Tabulation of costs and waste removals per plant, and cost per pound removed expressed as ranges to prevent indirect 

disclosure of data claimed as Confidential Business Information (CBI). 2 - Number of plants currently operating. No processors with direct dischargers currently operate in Anchorage; therefore, they 

have no costs or removals. A few processors are discharging to publicly owned treatment works (POTW). 3 - Pounds of fish processing waste removed. 4 - Possible processing plants closures or firm failures.

As shown in Table 1, the cost per pound removed in the petitioning locations ranges from $0.02 to 

$0.04/lb with the average being $0.03/lb. Because three canneries in one location are already using byproduct recovery for a very large portion of their waste, the incremental costs to meet non-remote 

requirements under either Scenario 1 or Scenario 2b for these facilities are very low. These figures do not 
Cost and Economic Impact Analysis for Alaska Seafood Processors

5

include the canneries which are already using by-product recovery for a very large portion of their waste.

In some locations, the cost per ton could be less under Scenario 2b given the assumptions of cooperation 

and sufficient existing by-product recovery capacity located nearby. These costs are very low and EPA 

concludes that considering the effluent reductions to be achieved they are reasonable.

For comparison, Table 2 provides an alternative annualized post-tax cost for these facilities, assuming all 

costs are annualized at the OMB-recommended discount rate of seven percent. In most cases, the discount 

rate calculated using the reported interest rates was lower than the seven percent OMB rate, due to the 

historically low interest rates offered in 2009. EPA ran the entire analysis using the generally higher 

OMB rate and found no difference in impact results that would change the outcome of the analysis. The 

annualized costs, as shown in Table 2, however, are slightly higher using the OMB rate. Total annualized 

costs are about $60,000 per year more under Scenario 1 and about $430,000 per year more under Scenario 

2b with the OMB discount rate. Differences in total annualized costs presented in Tables 1 and 2 reflect 

rounding of costs for each location prior to summation as presented in Table 1.

Table 2. Petitioning Locations: Aggregate Annualized Pre-Tax Facility Costs for Scenarios 1 

and 2b using Survey Reported Discount Rates and OMB's Recommended 7 Percent

Discount Rate ($2010, thousands)

Facility Classification

Aggregate Total 

Annualized Costs Using 

Survey Discount Rates (if 

available) 

Aggregate Total 

Annualized 

Costs Using OMB's 7% 

Rate

Scenario 1 Scenario 2b Scenario 1 Scenario 2b 

Pre-tax Costs to All Facilities $1,175 $4,964 $1,244 $5,454 

Post-tax Costs to All Facilities $795 $3,129 $855 $3,559 

Table 2 presents the capital costs, operating and maintenance (O&M) costs, estimated by-product 

revenues, and the annualized pre-tax and post-tax costs in the four petitioning locations to meet the nonremote wastewater control requirements under the two scenarios. The costs are annualized in this analysis 

using the survey-reported, nominal interest rates, adjusted by a presumed future inflation rate of two 

percent to create an estimated real discount rate. Where an interest rate was not provided, EPA used the 

OMB-recommended discount rate of seven percent (OMB, 2003). As the table shows, overall, Scenario 1 

is less expensive than Scenario 2b given the assumptions of cooperation and sufficient existing byproduct recovery located nearby are true under Scenario 2b. However, this is not necessarily true on a 

facility-by-facility basis or for all processing locations. Costs for scenario 2b were higher for locations 

where sufficient existing by-product recovery capacity does not exist for all processors. In these cases, 

higher costs reflect EPA estimates for new by-product recovery facilities with sufficient capacity for

processors in these locations.

The annualized post-tax costs in Table 1 and 2 are estimated under the assumption that the facilities will 

be able to expense the O&M costs and deduct the depreciation for their capital costs, thus, saving on 

income taxes; i.e., there is a tax shield on these items, and thereby lowering the actual cost to the facility. 

The cost annualization model incorporates the modified accelerated cost recovery system (MACRS), 

which specifies the percentage of a capital expenditure that can be depreciated every year. EPA chose a

time frame of 10 years for depreciation and for the analysis time frame as a whole. The 10-year analytical 

time frame is conservative because although some costs to meet the requirements would likely be 

depreciated over 10 years, other capital costs are for buildings and land, which would be depreciated over 

a longer period. However, extending the time frame for depreciation to, for example, 15 years, would 

have reduced the post-tax annualized costs used to assess impacts.
Cost and Economic Impact Analysis for Alaska Seafood Processors

6

2.2 Financial Impacts on Facilities in the Petitioning Locations

2.2.1 Baseline Analysis

Before EPA could determine the financial impacts on facilities in the petitioning locations, EPA analyzed 

the facilities’ financial health in the baseline prior to imposing additional costs for wastewater treatment 

faciilities. This analysis was undertaken for two reasons. First, EPA wanted to identify any trends in the 

financial data that would need to be accounted for in the projections. Second, EPA wanted to determine 

whether any facilities were not viable in the baseline. Any facilities considered baseline closures, where 

cash flow was less than $0 over the time frame of the analysis, cannot be analyzed further at this level of 

the analysis. In cases where the facility and the firm are the same entity, a baseline closure is assumed to 

be a firm failure. As discussed in the methodology (see Appendix A), the approach for analyzing the 

financial viability of facilities is a discounted cash flow analysis.

To construct the discounted cash flow analysis, EPA primarily used the Section 308 survey data provided 

for facilities. For facilities owned by multi-facility firms, EPA used the equation “Total Revenue – Total 

Facility Costs + Depreciation” in each year as a proxy for cash flow as reported in the Section 308 survey

responses. Essentially, this is earnings before interest, taxes, depreciation, and amortization (EBITDA). 

For single-facility firms, however, where interest payments could be included in the facility-level 

analysis, total facility costs included interest payments representing EBTDA as reported in the tax forms 

and annual reports provided by the respondents as part of their survey response. EPA’s assessment of the 

financial data did not indicate any easily identifiable financial trends across all facilities, and the facilities’ 

finances represented both better and worse years. Therefore, EPA determined that projecting the same 

patterns of better years and poorer years into the future is a reasonable projection method and avoids any 

assumption that facilities could grow their way out of any financial difficulties in the future. The cash 

flow estimates for each year, 2005 through 2009, are repeated for 2010 through 2019, based on the 

assumption that the facilities’ performance in the recent past is indicative of future years’ performance. 

EPA converted all financial values in each year to 2009 dollars (used in this analysis to represent 2010 

dollars) through the producer price index (PPI) for seafood processors (Bureau of Labor Statistics, 2010).

To discount these cash flows over the period of the analysis, EPA used the interest rates reported by the 

survey respondents, adjusted for a presumed inflation rate of two percent. Where interest rates were not 

reported, EPA used the OMB recommended real discount rate of seven percent as discussed earlier in 

Section 2.1. The present value of the cash flow is calculated over the 10-year period and then annualized 

to provide an estimate of the average annual cash flow at each facility. Other facility-specific 

methodology is provided in the CBI version of this report (U.S. EPA, 2011a).

No facilities are considered baseline closures; all are estimated to have positive annualized cash flow over 

the 10-year period of analysis. 

2.2.2 Post-Compliance Analysis

In the post-compliance analysis, the annualized post-tax costs of the non-remote ELG BPT effluent 

limitations requirements under Scenario 1 and Scenario 2b are subtracted from the annualized cash flows. 

All facilities in the analysis continue to have positive cash flow under Scenario 1.

 

Where cash flows are still positive post-compliance, the facilities are providing sufficient returns to cover 

their costs of capital. Cash flow analysis does not account for possible cash needs above returns on 

investment. The cash need of concern is capital replacement, which encompasses investments that are not 

expensed and captured in O&M costs. Capital replacement, however, is an exceedingly difficult item to 
Cost and Economic Impact Analysis for Alaska Seafood Processors

7

determine.4 As an alternative, EPA calculated the annualized post-tax costs as a percentage of cash flow. 

Later, in Section 4, EPA explores another method for estimating capital replacement that was not 

considered useful. 

Generally, under Scenario 1, EPA determined that annualized costs are a relatively small portion of total 

annualized cash flow; therefore, the cash flow remaining should be adequate to continue to provide for 

capital replacement. The major capital investments in seafood processing facilities are buildings and 

docks, which tend to be repaired, with costs captured in O&M costs, and are not replaced frequently; and 

land, which is irrelevant to capital replacement. Automated equipment is more likely to need to be 

replaced, but has a relatively long life and might not be replaced during the time frame of the analysis. 

Other costs might be incurred for capital improvements, for example, when a facility adds automated 

equipment that does not replace existing equipment.5 Given that ongoing maintenance is captured in the 

projected O&M costs, buildings are rarely replaced, and capital outlays strictly for replacement are only a 

portion of total capital outlays a facility might make, a relatively small buffer for capital replacement is

estimated to be needed, and EPA concludes that all buffers shown are adequate over the time frame of 

analysis. 

Given the relatively minor impacts on cash flow seen at most of the facilities, EPA considers the impacts 

on one non-surveyed, non-modeled facility likely to be similar to those shown for other surveyed facilities 

in the analysis, with costs as a percentage of cash flow within the ranges shown.

2.3 Impacts on Firms Owning Facilities in the Petitioning Locations

This section first discusses the overall impacts on firms owning facilities in the petitioning locations in 

Section 2.3.1. Section 2.3.2 then discusses the impacts to small firms (as defined by the Small Business 

Administration [SBA]) relative to those at large firms (Code of Federal Regulations, 2010).

2.3.1 Impacts on All Firms 

A total of nine firms own facilities in the petitioning locations (six surveyed and three non-surveyed 

firms). These firms range from large, multi-facility firms to small, single-facility firms. EPA assessed 

firms without data from survey questionnaire responses qualitatively as discussed at the end of this 

section. Before impacts on all firms in the petitioning locations are discussed, the section discusses the 

baseline analysis. The post-compliance impacts from both Scenario 1 and Scenario 2b are then discussed.

2.3.1.1 Baseline Analysis

Before undertaking the baseline analysis for the firm failure analysis, EPA reviewed the applicability of 

Altman’s Z to a financial analysis of the potentially affected seafood processing firms. Altman’s Z, a 

multivariate equation that combines various key financial ratios, provides weights for those ratios based 

on empirical data to define a likelihood of bankruptcy (Altman and Hotchkiss, 2006). This equation, 

therefore, is generally believed by investors to be a reasonable approach for determining financial health, 

particularly when some financial ratios appear to indicate financial strength, while others appear to 

indicate weakness. The original Altman’s Z was designed to judge the financial health of publicly held 

 4

 EPA has attempted to ask survey respondents in other surveys what their capital replacement costs have been in 

past years (U.S. EPA, 2005) but found that large, sophisticated multinational firms had extreme difficulties 

identifying capital replacement costs. Therefore, the much smaller firms with potentially less access to sophisticated 

accounting expertise in the Alaska seafood industry might not be able to identify these costs. 5

 Including capital improvements would require changing the baseline analysis as well. Because EPA is creating a 

snapshot in time based on the survey responses, this would be problematic. Also, capital improvements could be 

seen to be discretionary.
Cost and Economic Impact Analysis for Alaska Seafood Processors

8

manufacturing firms, but Altman modified this equation for use with private firms and this private firm 

equation is known as Altman’s Z ́ (Altman and Hotchkiss, 2006). EPA is using the equation developed 

for privately held firms, since the firms in this analysis are either privately held or, effectively, privately 

held; that is, they are not traded on major stock exchanges and do not file annual reports with the Security 

and Exchange Commission.

EPA first reviewed the results of the Altman’s Z ́ analysis to determine its to these firms. If firms were 

identified as financially unhealthy year after year, but bankruptcy did not occur, this approach would be 

considered unreliable for the firms in question. However, none of the firms were identified as unhealthy 

in any of the years for which data were available, so the equation does not seem to be unreliable based on 

this definition of reliability. Furthermore, when EPA reviewed the financials line by line and in more 

detail, the Z ́-score results were not at odds with the more qualitative assessment of financial health.

The equation for the Z ́ Score is:

0.717*(Current Assets-Current Liabilities)/Total Assets + 0.847*Retained Earnings/Total 

Assets + 3.107*EBIT/Total Assets + 0.42*Equity/Total Liabilities+ 0.998*Sales/Total Assets

where EBIT is Earnings Before Interest and Taxes6

A Z ́-Score greater than 2.9 is considered healthy; between 1.23 and 2.9 is considered indeterminate; and t

less than 1.23 is considered to represent distress, with the firm considered likely to fail. EPA interprets a 

baseline score above failing as a non-failing firm in this analysis, which is the same approach used in 

other effluent guidelines analyses (see, e.g., the Economic Analysis for Industrial Laundries (U.S. EPA, 

2000)). 

EPA also investigated cash flows to add to the understanding of financial health. EPA calculated firmlevel discounted cash flow calculated using 2005 to 2009 financial information as provided by firms and 

the same assumptions and procedures as the facility-level discounted cash flow analysis. These included

respondent-provided interest rate adjusted for inflation or the seven percent discount rate, and firmprovided financial data inflated to 2009 dollars using the PPI for seafood processors. Certain other 

facility-specific considerations are discussed in the CBI version of this report (U.S. EPA, 2011a). The 

2005 through 2009 cash flow estimates are repeated in years 2010 through 2019 for all firms, based on 

the assumption that a firm’s performance in the recent past is indicative of future performance. Because 

many firms did not provide enough information to deduce income taxes, all cash flows are computed pretax. All firms have positive discounted cash flow and so no firms are considered to be baseline failures. 

The discounted cash flow for firms is not adjusted for capital replacement. All firms are estimated to have 

positive cash flow over the time frame of the analysis, assuming the next 10 years are not vastly different 

from the previous five years in terms of financial conditions.

2.3.1.2 Post-Compliance Analysis

In this analysis, the applicable costs to all facilities owned by a firm in the petitioning locations are 

summed, and the financial situation at each firm is adjusted to account for the change in key line items 

used to compute the Altman’s Z ́ score. To develop the post-compliance financial state, EPA used the 

capital costs to adjust assets upwards and liabilities downwards under a simplifying assumption that the 

cost is covered by borrowed monies. EPA also adjusted EBIT by the annualized sum of depreciation and 

O&M costs as calculated by the cost annualization model (see Appendix A for more information). Only 

 6

 EBIT is essentially a calculation of business operating income (includes depreciation and does not consider other 

investments) before interest expenses or taxes are deducted. 
Cost and Economic Impact Analysis for Alaska Seafood Processors

9

the 2009 finances are adjusted in the post-compliance analysis because the Altman’s Z ́ analysis is usually

performed on the most recent year of data to predict financial stability going forward. 

EPA determined that the changes to the Z ́ score are generally very modest under Scenario 1, indicating 

that the costs are small relative to the financial size of most of these firms. 

Given the impacts seen at most of the firms in this analysis, EPA tentatively considered the impacts on 

two non-surveyed, non-modeled firms are likely to be similar to those for other firms in the analysis. The 

only petitioning location facility under the ownership of one of these processors is already processing 

much of its waste through a by-product recovery facility and is expected to incur minimal costs. One 

processor is much smaller than other surveyed firms, and its costs should be commensurate with its size. 

Furthermore, EPA has no data or information to indicate these firms are less healthy than the firms 

analyzed quantitatively. Rather, where EPA has specific data for both small and large firms in this 

industry, they are generally considered capable of complying with requirements based upon screening 

(Scenario 1) while remaining economically viable going forward.

2.3.2 Impacts on Small vs. Large Firms

Small firms in this industry are those with fewer than 500 employees averaged over the year. Of the firms 

surveyed, some meet the definition of a small firm. For the surveyed small firms, annualized post-tax 

costs as a percentage of revenues for Scenario 1 are small, less than 0.5 percent for all small firms in the 

analysis (EPA 2011a). Therefore, EPA concluded the costs incurred by small firms would be reasonable 

and affordable.

3. Costs and Impacts to Facilities and Firms in the Non-Petitioning 

Locations of Interest

Section 3 discusses the annualized costs to the surveyed and modeled facilities in the nonpetitioning locations and provides the total costs to all facilities in the petitioning locations 

(Section 3.1). Section 3.2 discusses the impact these costs have on those facilities and determines 

whether any facilities might be forced to close if they are required to meet the non-remote BPT 

effluent limitations as promulgated for processors in petitioning locations. Section 3.2 concludes 

with the impacts on the owner firms of those facilities. Costs for multiple facilities are 

aggregated to multi-facility firms, and all firms are then analyzed to determine whether the costs 

of these requirements could contribute to potential firm failure. Appendix A describes the 

methodologies used in the analyses discussed below in detail. To determine whether facilities 

and firms in the non-petitioning locations of interest could afford to meet non-remote wastewater 

control requirements, EPA ran the same analyses as described above for petitioning locations to 

estimate annualized costs and impacts on facilities and firms in the Kenai Peninsula and Sitka, 

among additional processing locations of interest.

7 As noted previously, Dutch Harbor is also 

being considered as an additional processing location. Because all three long-standing processors 

at this location already operate screening technology and comply with the BPT effluent 

limitations, there are no costs necessary for this location. Therefore, there is no further discussion 

of Dutch Harbor in this analysis.

 7

 EPA identified several facilities as not currently operating as seafood processors or not likely to discharge. (U.S. 

EPA, 2013a). 
Cost and Economic Impact Analysis for Alaska Seafood Processors

10

3.1 Annualized Costs to Facilities in the Locations of Interest

EPA surveyed four facilities in these additional locations of interest and was able to quantitatively 

analyze costs for six non-surveyed facilities using cost estimates developed from the processing 

facility most closely resembling the facility being modeled (e.g., size based on total production, 

etc.). 

Table 3 presents the results of the cost annualization (U.S. EPA 2013 a,b). Because Sitka facilities are 

included in the costs for Scenario 1 and not in the costs for Scenario 2b, the costs for Scenario 2b are 

much lower than those for Scenario 1 in the locations of interest. This is true because a facility has been 

proposed (Sitka Meal Oil and Gelatin - SMOG) with sufficient capacity to serve at least the processors in 

this location and possibly other locations within reasonable distance by vessel. However, it is true that, 

generally, costs under Scenario 2b for facilities in the Kenai Peninsula are estimated to be the same as or 

lower than the costs under Scenario 1 under the assumptions of cooperation and sufficient existing byproduct recovery capacity located nearby.

Table 3 presents a summary of results discussed above for additional non-petitioning processing locations 

being considered by EPA. Other locations than those listed below may be considered based upon 

information and data included in comments submitted on the NODA.

Table 3. Summary of Results for Additional Non-Petitioning Processing Locations1

Location Number of 

Plants 2

Total 

Annualized 

Cost per Plant -

million $

Removals per 

plant - lbs/yr 3

(millions)

$/lb removed Economic 

Impact 4

Dutch Harbor 3

<0.10 1 - 3 0.04 - 0.07

No

Kenai 

Peninsula 10 No

Sitka 3 No

Total - all 

Plants 16 <$0.90 <15 $0.06 -

1 - Tabulation of costs and waste removals per plant, and cost per pound removed expressed as ranges to prevent indirect 

disclosure of data claimed as Confidential Business Information (CBI). 2 - Number of plants currently operating. In Dutch Harbor, all three processors that have operated consistently have screening and 

individual by-product recovery in place and thus comply with effluent limitations based upon screening. Three additional 

processors have operated only intermittently in Dutch Harbor. Thus no costs or removals were developed and no 

economic analyses were performed for Dutch Harbor. 3 - Pounds of fish processing waste removed. 4 - Possible processing plants closures or firm failures.

The cost per ton for the additional locations of interest is marginally higher than those for the petitioning 

locations under Scenario 1. However, Scenario 2b costs per ton for the Kenai Peninsula facilities are 

generally within the range of cost per ton seen for the petitioning location facilities under Scenario 1. 

Sitka facilities, for which EPA only estimated costs for Scenario 1, are estimated to incur costs per ton 

similar to those for the petitioning locations under Scenario 1. However, due to the lack of survey data in 

this location, EPA does not draw any quantitative conclusions at this time regarding whether Sitka 

facilities costs per ton are in the same range as those faced by the facilities in the petitioning locations 
Cost and Economic Impact Analysis for Alaska Seafood Processors

11

under Scenario 2b. Nonetheless, EPA estimates these costs are also very low because these processors are 

similar to processors in other locations for which costs and removals were developed based upon survey 

questionnaire responses. EPA concludes that considering the effluent reductions to be achieved these 

costs are reasonable for the additional non-petitioning processing locations.

3.2 Financial Impacts on Facilities and Firms in the Locations of 

Interest

EPA’s analysis shows that all surveyed and modeled facilities in the locations of interest are considered 

viable in the baseline. All are estimated to have positive annualized cash flow over the 10-year period of 

analysis. In the post-compliance analysis, all analyzed facilities are able to afford the costs of Scenario 1 

and Scenario 2b. Costs as a percentage of cash flow are small. The baseline firm-level analysis indicates 

that all firms analyzed are considered viable in the baseline. No firms are considered likely to fail under 

either Scenario 1 or Scenario 2b. Changes in the Altman’s Z ́ ratios are small, and cash flows are still 

positive and change relatively little under either scenario.

EPA’s analysis also shows that impacts on small firms are minimal. Impacts on the basis of compliance 

costs to revenues are less than 0.5 percent. Given that no major impacts are seen for small surveyed firms 

or for any large firms, the impacts on small firms also are considered minimal.

Based on these observations, and the observations that the other surveyed and modeled firms and facilities 

in the petitioning locations are not expected to experience closures or firm failures under Scenario 1, EPA 

extended the analysis, qualitatively, to the two facilities and four firms not analyzed quantitatively. EPA

tentatively considered the impacts on the non-surveyed, non-modeled firms and facilities likely to be 

similar to those shown for other firms and facilities in the analyses under the two scenarios, with costs as 

a percentage of cash flow probably lying within the ranges shown for facilities. Moreover, EPA expects 

firm-level results for analyzed firms also to be similar at firms that were not analyzed.

4. Additional Analyses

Two additional analyses are provided in this section. The first presents a barriers-to-entry analysis, which 

investigates whether new facilities in the petitioning locations or the additional locations of interest, could 

meet the requirements, or whether those requirements might discourage the establishment of new firms or 

facilities in these regions. The second analysis presents an alternative method of determining whether 

post-compliance cash flows would adequately cover capital replacement (Section 4.1).

4.1 Barriers to Entry

The foregoing analyses have shown that existing facilities and firms can afford the basic requirements 

represented in Scenario 1. New facilities in these areas of Alaska are often existing facilities that are 

acquired and brought back on line by new or established firms. Thus, these types of “new” facilities can 

be assumed to be reasonably represented by existing facilities. Because all existing facilities are shown to 

be able to afford Scenario 1 costs, newly re-established facilities should also be able to afford these costs. 

One barrier to entry analysis that EPA has also used in the past to determine whether barriers to entry 

exist is an assessment of whether the capital costs of the additional equipment is a substantial portion of 

the costs to construct a new facility (see, e.g., U.S. EPA, 2006). If the capital cost for the additional 

equipment is well within the usual engineering contingencies built into construction cost estimates, EPA 

has determined that the cost of a rule poses no barriers to entry. EPA estimated construction costs of a 

typical new facility (U.S. EPA, 2011a) and concluded that the costs to add Scenario 1 equipment would 

have been a small portion of typical contingencies. Furthermore, the cost to design-in equipment is 

usually less expensive than the cost to retrofit it. The barrier to entry to new seafood processing facilities 
Cost and Economic Impact Analysis for Alaska Seafood Processors

12

in any of the locations investigated is, therefore, considered very small incremental to any existing 

barriers to entry.

4.2 Alternative Method for Assessing Adequate Cash Flow for Capital 

Replacement Needs

EPA also performed an alternative method for estimating capital replacement costs at firms where facility 

assets are known at single-facility firms.8 In this analysis, capital replacement costs were set at 10 percent 

of firm-level assets for the single-facility firms. This approach generally has no effect on the outcome of 

the analysis. However, EPA does not believe that the capital replacement estimate generated this way is a 

satisfactory approach, given that firms with newer facilities would tend to have higher assets and a lower 

immediate capital replacement need and firms with older facilities and fully depreciated assets would 

likely have higher capital replacement needs. Thus, EPA chose not to use this method for estimating 

baseline cash flows.

 8

 Including the firms treated as single-facility firms.
Cost and Economic Impact Analysis for Alaska Seafood Processors

13

5. References

Altman, Edward I. and Edith Hotchkiss, 2006. Corporate Financial Distress and Bankruptcy. Hoboken: 

John Wiley & Sons, pp. 240-249.

Bureau of Labor Statistics, 2010. Databases, Tables & Calculators by Subject, “Producer Price Index 

Industry Data,” Seafood product preparation and packaging. Accessed 9 Nov 2010. 

http://data.bls.gov/ppi/#tables.

Code of Federal Regulations (CFR), 2010. CFR 13 Part 121. Small Business Size Regulations.

Internal Revenue Service (IRS) 2010. How to Depreciate Property for Use in Preparing 2009 Returns. 

Publication 946.

Office of Management and Budget (OMB), 2003. Circular A-4, Subject: Regulatory Analysis, November 

2003.

U.S. EPA, 2000. Economic Assessment for the Final Action Regarding Pretreatment Standards for the 

Industrial Laundries Point Source Category (Revised March 2000). EPA Office of Water, EPA 821-R-00-

004. 

U.S. EPA, 2005. Survey Questionnaire to Determine the Effectiveness, Costs, and Impacts of Sewage and 

Graywater Treatment Devices for Large Cruise Ships Operating in Alaska. (DCN 00413)

U.S. EPA, 2006. Economic and Benefits Analysis for the Final Section 316(b) Phase III Existing 

Facilities Rule. EPA-821-R-06-001. June 1.

U.S. EPA, 2002. Economic Analysis of the Final Revision to the National Pollutant Discharge 

Elimination System Regulation and the Effluent Limitations Guidelines for Concentrated Animal Feeding 

Operations. EPA-821-R-03-002. December.

U.S. EPA. 2010. Questionnaire for Canned and Preserved Seafood Processing Facilities in Certain 

Locations of Alaska. April. Available at

http://water.epa.gov/scitech/wastetech/guide/upload/survey.pdf.

U.S. EPA, 2011a. Final Costs and Impact Analysis for Alaska Seafood Processors (Facilities and Firms). 

December (CBI). (DCN 00409)

U.S. EPA, 2013a. Profile of the Alaska Seafood Processing Industry. August. (DCN 00412)

U.S. EPA, 2013b. Report of Quality Activities Supporting Alaska Seafood Processing Cost Estimates,

August. (DCN 00499)
Cost and Economic Impact Analysis for Alaska Seafood Processors

14

Appendix A

Methodologies Used to Analyze Costs and Impacts on 

Seafood Processing Firms and Facilities

This Appendix presents the approaches used to analyze the Section 308 survey data. It discusses the 

methods for:

• Analyzing the current financial situation facilities and their firms in the five petitioning 

locations.9

• Estimating financial impacts on these firms and facilities from meeting the final ELGs for waste 

streams that are currently being discharged nearshore under two waste management scenarios. 

• Analyzing small business impacts.

• Analyzing average scenario costs per ton of waste generated among the various locations.

• Analyzing barriers to entry.

• Providing a sensitivity analysis for cash flow analysis.

EPA did not develop further analyses to assess impacts on employment and broader impacts on 

communities because no facility and firm analyses predicted incremental closures or firm failures.

The analyses are discussed in the three following sections. Section A.1 discusses the initial baseline 

facility- and firm-level analyses that were performed prior to full model development, which focused on 

evaluating the baseline conditions at 14 identified facilities in the petitioning locations and their six firms 

that are currently discharging their wastewater in the petitioning locations. Section A.2 also discusses the 

analyses that that were done to assist in selecting the appropriate methodologies, given the available data.

Section A.2.1 discusses a preliminary step to identify appropriate models for the facilities and firms in the 

petitioning locations that were not surveyed. Section A.2.2 then discusses the preliminary baseline 

analysis and the additional analyses used to refine the baseline analysis methodology. Section A.2.3 

discusses the possible methodologies for analyzing impacts on the firm level and presents the choice of 

methodology and the rationale for this choice, based on the initial results of the baseline firm analysis.

Section A.3 discusses the data, computations, and analyses used to integrate the costs calculated for the 

two waste management scenarios into the modeling to analyze the post-compliance changes in financial 

conditions at the affected facilities and firms, the methods for calculating those changes in financial 

conditions, the decision criteria used to identify changes in financial conditions that are considered to 

indicate an economic impact, and the extension of all of these analyses to an additional group of facilities 

and firms in two other locations of interest, the Kenai Peninsula and Sitka. 

Section A.4 discusses additional analyses, including the methodologies used for a small business analysis

and an analysis used to compare average cost per ton of waste generated in both petitioning locations and 

the two analyzed locations of interest.

 9

 No discharging facilities currently are located in Anchorage, however; facilities and their firms located in 

Cordova, Juneau, Ketchikan, and Petersburg continue to be affected by an EPA decision and are analyzed.
Cost and Economic Impact Analysis for Alaska Seafood Processors

15

A.2 Preliminary Baseline Analysis

Prior to constructing a full, operational economic impact model, EPA hand-extracted the key financial 

data from the Section 308 survey questionnaire data submitted by the firms and their facilities that were 

located in the petitioning locations to develop a preliminary baseline analysis of facilities and to test 

possible approaches for analysis at the firm level. EPA began a preliminary analysis of baseline 

conditions for the 14 processors and their firms identified as dischargers that are located in the petitioning 

locations prior to receiving electronic survey data because of the limited number of surveys involved. 

A.2.1 Modeling Decisions for the Petitioning Location Facilities and Firms

The first step in analyzing the baseline health of the petitioning location facilities and firms was to assess 

how to model the few facilities that were not surveyed. The Section 308 survey provided information on 

11 of the 14 discharging facilities in the petitioning locations. All but one of the 14 was analyzed 

quantitatively. Two facilities were considered similar to others of the 11 surveyed and financial data for 

these two facilities was drawn from certain of the other facilities. The 11 surveyed facilities are owned by 

six surveyed firms, with a total of nine firms owning facilities in the petitioning locations where discharge 

is still occurring. These similarities were assessed using information from NPDES reports and other data 

(U.S. EPA, 2013a,b).

Later in the model development, EPA added the Kenai Peninsula and Sitka facilities and firms. Ten 

facilities were identified as operating in the Kenai Peninsula location (see U.S. EPA 20131a,b).10 Five of 

these were surveyed and EPA has concluded that another four non-surveyed facilities resemble at least 

one of the facilities that was surveyed. The four non-surveyed facilities in the Kenai Peninsula resemble

another facility and have been assigned financial information for that facility. None of the three Sitka 

facilities or their firms was surveyed, although EPA has concluded that two of the facilities are similar to 

surveyed facilities in other locations (U. S. EPA 2013a,b). Another processor in Sitka is much larger in 

terms of quantities of seafood processed than any facility processing only fresh and frozen seafood. Thus, 

it is not assigned model facility financials and is analyzed qualitatively. At the firm level, no firms were 

considered to resemble the owner firm. Therefore, three facilities in Sitka were analyzed qualitatively. To 

calculate aggregate costs, however, costs were assigned to the facilities that were not modeled financially 

or analyzed quantitatively.

These facilities and firms did not play a role in the development of the methodologies but those that could 

be analyzed were added into the analyses using the same methodologies as described for the petitioning 

location firms and facilities in the following sections. Costs for all facilities, regardless of whether they 

could be modeled financially, are added into aggregate cost calculations.

A.2.2 Preliminary Baseline Facility-Level Analysis

EPA selected a discounted cash flow (DCF) approach at the facility level as the measure of financial 

health, which is used in many other economic analyses of effluent guidelines (see, e.g., U.S EPA, 2002). 

In DCF analysis, cash flow in each year is discounted to its present value, which is its value in the first 

year of analysis, given that a dollar today is worth more than a dollar tomorrow. Usually, the discount rate 

is either the reported interest rate or cost of equity incurred by an entity to borrow or use its own money to 

fund a capital project, adjusted for inflation to create a real cost of capital, or alternatively, the Office of 

Management and Budget recommends a real cost of capital of seven percent. The cash flow is 

approximated, typically, by using total revenues minus total costs, and adding back in depreciation, 

because depreciation is a non-cash item in the total costs line item. Cash flow is considered by most 

financial analysts as a key determinant of financial health at a facility or at a firm. 

 10 EPA identified several facilities as not currently operating as seafood processors or not likely to discharge. (U.S. 

EPA, 2013a). 
Cost and Economic Impact Analysis for Alaska Seafood Processors

16

Operating earnings are used for facilities generally as a proxy for cash flow. Total operating earnings are 

defined as total operating revenues minus total operating costs, which exclude overhead costs, interest, 

taxes, and depreciation—usually line items kept on books only at the firm level at multi-facility firms. 

Although most of the facilities owned by multi-facility firms were expected to report only operating 

earnings, several submitted information on depreciation that could be used to adjust total outlays to a cash 

flow approximation. These profit centers, where a full income statement was available at least through 

earnings before taxes [EBT], were analyzed using EBT plus depreciation as a proxy for cash flow 

(EBTDA). Additionally, all single-facility firms, or those operating their books as single-facility firms,

11

were handled in this same way. For the facilities where only operating earnings were reported, cash flow 

was approximated using operating earnings alone. 

The equation used, therefore, to calculate annual cash flow was Total Facility Revenues – Total Facility 

Costs (including interest, where possible) + Depreciation (where available). The next step in calculating 

DCF was to put all dollar values of the financial information extracted on a 2009 basis and extrapolating 

this data over the 10-year period of analysis. EPA chose the 10-year period because EPA uses it 

frequently for analysis, and because the equipment needed for compliance was considered to have a life 

of at least 10 years. Longer analysis periods usually do not change the basic results and financial 

projections become more uncertain as the timeframe of the analysis is extended. The estimated annual 

cash flow and/or operating earnings reported in each year were inflated to 2009 dollars using the Producer 

Price Index for Seafood Processors (BLS, 2010). Because the Alaska seafood processing industry is a 

major contributor to the U.S. economy within this sector (see U.S.EPA, 2013a), EPA considered the PPI 

for this industry as the best inflator to use. These earnings/cash flow were then extended out 10 years; i.e., 

under an assumption that the last five years of financial data are reasonably representative of the next 10 

years, and discounted using either seven percent or the owner firm’s reported current interest rate after 

conversion to a real rate. EPA evaluated trends following calculation of each facility’s DCF (see below).

EPA needed to address a few data gaps prior to running the DCF analysis. EPA estimated total revenues, 

total facility costs, and depreciation values for years 2005, 2006, and 2007 for one facility, which was 

acquired in 2008. EPA used the facility’s 2008 data, which was the first year of available data and 

calculated the previous years’ data by assuming that the percentage changes in costs and revenues would 

have been similar to those experienced by other facilities in the same location in those years. EPA also 

created assumed total revenues and total facility costs for another facility for 2005 and 2006, which were 

assumed identical to those in 2007 for reasons that are CBI (see U.S. EPA, 2011a). These data 

imputations allowed EPA to use the same projection method for these two facilities used for the others. 

EPA assigned $0 cash flow in 2010 to a facility that EPA knew had been temporarily closed that year, 

which was the year following the last year of submitted data. EPA projected all other data in the same 

way as described earlier. 

To calculate DCF over 10 years EPA used Excel’s NPV function, which uses each year’s annual cash 

flow, in this case, 10 years of annual cash flow, and a discount rate to calculate the present value (PV) of 

that cash outflow. EPA used the seven percent OMB-recommended discount rate for all facilities in the 

preliminary analysis for simplicity (OMB, 2003).

 11 Several facilities are treated as one facility financially because that is the way the firms provided the data in the 

survey.
Cost and Economic Impact Analysis for Alaska Seafood Processors

17

Baseline conditions for the facility analysis were assessed as follows:

• If the PV of the discounted cash flow/earnings (DCF) was positive regardless of the type of 

facility, the facility would be considered healthy in this preliminary analysis.12

• If the PV of DCF for one facility of a multi-facility firm was negative, the facility is 

considered a cost center, even if reporting EBT. If this occurred, EPA would not analyze 

such facilities further. Later (see Section A.2.3), EPA analyzed the owner firms of all 

facilities. If the firm was considered healthy, any facility considered non-viable in the 

baseline would not be considered a baseline closure, but considered to be operating as a cost 

center.

• If the PV of DCF at a firm-facility was negative, the firm and its one facility would be 

considered a baseline firm failure/facility closure.

Note that this analysis was preliminary. Other considerations that were addressed include whether any 

trends might indicate that a mapping of five years of prior cash flow to a projection of cash flow over the 

10-year time frame is unrealistic, and the extent to which cash flows calculated at firm-facilities might 

need to be adjusted to allow firms to maintain their current level of business; i.e., to allow for capital 

replacement. Additionally, EPA added a component to the model that allowed the Agency to choose 

whether to use the seven percent OMB discount rate or the Section 308 survey questionnaire reported 

interest rates, and tied the facility analysis to the firm-level analysis. This latter step will be discussed 

below in Section A.2.3.

EPA qualitatively assessed trends by determining whether the facilities as a group seemed to have annual 

earnings that seemed to rise or fall over time, but no clear direction either up or down overall was seen in 

the data, although some individual facilities showed some trends in one direction or another. Additionally, 

because five years of data was available in most cases, EPA believes that the data captured provide a 

reasonable representation of the relatively unpredictable boom and bust cycles common to the industry 

(see EPA, 2013a). Therefore, EPA believes the five years of data are the best predictor available of the 

next 10 years financial picture at the surveyed firms and facilities.

EPA also investigated what data might be available to adjust cash flow to account for capital replacement 

needs at the facilities. In recent years, OMB has been concerned that a positive PV of DCF postcompliance is not sufficient to allow the firm to continue as an ongoing business as it appears in the 

snapshot of the Section 308 Survey. EPA recently has looked at capital replacement costs, which are costs 

beyond those captured in typical maintenance costs, to adjust cash flow (see U.S. EPA, 2005). This 

adjustment allows a certain amount of cash to be set aside for major replacement investments, such as a 

new boat to replace an older boat for delivery of seafood to the processor. However, the acquisition of a 

new boat to expand the firm’s access to seafood would not be considered capital replacement. Such 

expenditure is not a cost incurred to allow the firm to continue as it is, but to grow and thereby, become a 

firm that is different from the one in the baseline. EPA was not able to develop a specific estimate of 

capital replacement for facilities, but does develop an approach in the post-compliance analysis (see 

Section A.3) that provides a sense of the impact on cash flow from the two scenarios analyzed. EPA also 

provides an alternative assessment of cash flow for firms in a sensitivity analysis (see Section A.4). 

 12 A firm might decide to close a small but economically viable plant if the processing capacity can be replaced with 

more efficient capacity. For example, a firm could make better use of unused capacity at a newer, more efficient 

plant or, if expansion is needed, the firm could opt to close the smaller, older plant and replace it with a larger, more 

efficient plant. These decisions are strategic decisions where the firm considers factors beyond whether the original 

plant is making a profit. Such closures, particularly if announced before EPA publishes the Final Response to 

Petition, should not be considered an impact of the rule.
Cost and Economic Impact Analysis for Alaska Seafood Processors

18

EPA prepared a toggle, which worked both in the facility- and firm-level models, that allowed the Agency

to use either the OMB seven percent discount rate for all firms and facilities or the Section 308 reported 

interest rates. The reported interest rates were adjusted using an assumed two percent inflation rate. The

computation of the real interest rate was thus the nominal reported rate minus two percent. Where interest 

rates were missing from the Section 308 data, EPA used the seven percent rate. EPA created the toggle 

because most of the reported interest rates reflected the very low interest rates available at this time. 

Because EPA is not certain whether such rates might apply in the future, the OMB rate was considered a 

reasonable upper bound of future real rates. Had any differences in impacts been estimated due to the use 

of the OMB rate, EPA would have used the OMB rate exclusively. 

A.2.3 Preliminary Baseline Firm-Level Analysis

EPA used its preliminary baseline firm-level analyses to help inform the choice of methodologies for 

analyzing firms. The baseline firm-level analysis is discussed below. First, EPA reviews the 

methodologies considered for analyzing firms, including the decision criteria for identifying firm-level 

impacts. 

A.2.3.1 Options Considered for Firm-Level Analysis

EPA considered three possible approaches for a firm-level analysis. Each of these approaches, or some 

combination of these approaches, has been used in previous economic analyses for ELGs (see, for 

example, U.S. EPA, 2000, 2002). These three approaches are as follows:

• Use of Altman’s Z ́ alone, which is an equation that can be used to predict bankruptcy at 

manufacturing firms. Altman’s Z ́ is described in detail in Section A.2.2.2.13

• Use of Altman’s Z ́, combined with a DCF analysis (DCF = net income plus depreciation) to 

possibly provide better predictive power where Altman’s Z ́ is indeterminate.

• A DCF analysis combined with an analysis of certain key financial ratios, if Altman’s Z ́

appears unsuitable for use with those firms whose major portion of business might be 

Alaska-based.

Advantages and Disadvantages of the Altman’s Z ́-only Approach 

The advantages include:

• EPA has relied on Altman’s Z ́ in previous ELG analyses.

• Altman’s Z ́ is useful in distinguishing financial health at firms where some financial ratios 

appear “good,” but others appear “bad” because it is a weighted linear function of several 

financial ratios and produces one number that can be compared to benchmarks established 

using empirical data. 

• Financial data to construct the Altman’s Z ́ equation are readily available in financial reports 

and, presumably, in the surveys.

 13 Because seafood processing is considered a manufacturing industry, EPA considered it possible to assess firmlevel financial health using Altman’s Z (or Altman’s Z’ for privately held firms). 
Cost and Economic Impact Analysis for Alaska Seafood Processors

19

The disadvantages include:

• Altman’s Z ́ results can lie in an indeterminate range.

• Location of some firms and much of the business of the other firms in Alaska could have an 

effect on the Altman’s Z ́ predictive power because the cost of doing business in Alaska is 

much higher, generally, than that in the lower 48.

Advantages and Disadvantages of a DCF Combined with Altman’s Z ́ Approach

The advantages of a DCF combined with Altman’s Z ́ are:

• DCF, in some form, is considered by many financial analysts to be the ultimate factor in 

determining the health of a firm.

• Might assist in a bankruptcy determination for firms with Altman’s Z ́ results in the 

indeterminate range.

The disadvantages are:

• If Altman’s Z ́ is not a good predictor for Alaska firms or firms with large business interests 

in Alaska, this approach might also continue to have predictive issues.

• DCF needs to be adjusted for other cash needs.14

Advantages and Disadvantages of a DCF, Combined with Financial Ratio Analysis 

The advantages of a DCF combined with financial ratios (see below in Section A.3.1.2) are:

• DCF advantages as discussed above.

• Financial ratio analysis has been used by itself to predict bankruptcy in other ELG analyses.

• Financial ratio analysis and DCF have been used together to predict bankruptcy in other 

ELG analyses.

• Financial ratio analysis provides a way of additionally quantifying moderate impacts on 

firms, that is, impacts short of failure.

• If DCF is adjusted to account for other cash needs, ratio analysis provides a way of 

distinguishing those who may be reinvesting and using all available cash flow but seem to 

have adequate access to additional capital; i.e., key financial ratios are strong, and those who 

are reinvesting and using all available cash flow but do might not have adequate access to 

additional capital. 

 14 In recent years, OMB has been concerned that a positive PV of DCF post-compliance is not sufficient to allow 

the firm to continue as an ongoing business as it appears in the snapshot of the Section 308 Survey. Recently EPA 

has looked at capital replacement costs (costs beyond those captured in typical maintenance costs) to adjust cash 

flow. This adjustment allows a certain amount of cash to be set aside for major replacement investments (such as a 

new boat to replace an older boat for delivery of seafood to the processor). However, the acquisition of a new boat to 

expand the firm’s access to seafood would not be considered capital replacement. Such expenditure is not a cost 

incurred to allow the firm to continue as it is, but to grow, and thereby become a firm that is different from the one 

in the baseline). EPA was not able to develop a specific estimate of capital replacement but as discussed later, 

provided a sensitivity analysis of cash flow cushions. 
Cost and Economic Impact Analysis for Alaska Seafood Processors

20

The disadvantages are:

• DCF cons as discussed above.

• Issues with ratios pointing to different conclusions remain.

• A benchmark identifying at which point a ratio indicates “poor” financial health is 

subjective

A.2.3.2 Approach Used

Before undertaking the baseline analysis for the firm failure analysis, EPA reviewed the applicability of 

Altman’s Z ́ to a financial analysis of the potentially affected seafood processing firms. Altman’s Z, a 

multivariate equation that combines various key financial ratios, provides weights for those ratios based 

on empirical data to define a likelihood of bankruptcy (Altman and Hotchkiss, 2006). This equation, 

therefore, is generally believed by investors to be a reasonable approach for determining financial health, 

particularly when some financial ratios appear to indicate financial strength, while others appear to 

indicate weakness. The original Altman’s Z was designed to judge the financial health of publicly held 

manufacturing firms, but Altman modified this equation for use with private firms and this private firm 

equation is known as Altman’s Z ́ (Altman and Hotchkiss, 2006). EPA thus selected the equation 

developed for privately held firms to evaluate the applicability of Altman’s Z ́ to this analysis, given that

the firms in this analysis are either privately held or, effectively privately held; that is, they are not traded 

on major stock exchanges and do not file annual reports with the Security and Exchange Commission.

EPA first reviewed the results of the Altman’s Z ́ analysis to determine the applicability of Altman’s Z ́ to 

these firms. If firms were identified as financially unhealthy year after year, but bankruptcy did not occur, 

this approach would be considered unreliable for the firms in question. However, none of the firms were 

identified as unhealthy in any of the years for which data were available, so the equation does not seem to 

be unreliable based on this definition of reliability. Furthermore, when EPA reviewed the financials line 

by line and in more detail, the Z ́ score results were not at odds with the more qualitative assessment of 

financial health.

The equation for the Z ́ Score is:

0.717*(Current Assets-Current Liabilities)/Total Assets + 0.847*Retained Earnings/Total Assets 

+ 3.107*EBIT/Total Assets + 0.42*Equity/Total Liabilities+ 0.998*Sales/Total Assets

where EBIT is Earnings Before Interest and Taxes15.

A Z ́ Score greater than 2.9 is considered healthy, between 1.23 and 2.9 is considered indeterminate, and 

lower than 1.23 is considered to represent distress, with the firm considered likely to fail. EPA interprets a 

baseline score above failing as a non-failing firm in this analysis, which is the same approach used in 

other effluent guidelines analyses (see, e.g., the Economic Analysis for Industrial Laundries (U.S. EPA, 

2000)).

Because of indeterminate Z ́ scores, which EPA considers likely to represent a “marginal” condition, EPA

also investigated cash flows to determine if they were positive or negative for any indeterminate firms. 

EPA calculated the firm-level discounted cash flow using 2005 to 2009 financial information as provided 

by firms. EPA also used the same assumptions and procedures as the facility-level discounted cash flow 

 15 EBIT is essentially a calculation of business operating income (includes depreciation and does not consider other 

investments) before interest expenses or taxes are deducted. 
Cost and Economic Impact Analysis for Alaska Seafood Processors

21

analysis, including respondent provided interest rate, adjusted for inflation or the seven percent discount 

rate, firm-provided financial data inflated to 2009 dollars using PPI for seafood processors. For one firm 

in 2005 and 2006 that did not provide data for those two years, EPA filled those years with data from 

2007. All other firms provided data for all five years. Another firm did not provide depreciation or 

interest figures. Therefore, this firm’s cash flow is based solely on the firm’s EBIT. For this one firm, 

thus, EPA is using depreciation as a proxy for capital replacement; depreciation could somewhat overstate 

or understate actual capital replacement needs (see also the sensitivity analysis using an assumed capital 

replacement value for firms as described in Section A.4). The 2005 through 2009 cash flow estimates are 

repeated in years 2010 through 2019 for all firms, based on the assumption that firms’ performance in the 

recent past is indicative of future years’ performance. Because many firms did not provide enough 

information to deduce actual income taxes paid, EPA computed all cash flows at the firm level, pre-tax. 

The DCF analysis and the Altman’s Z ́ analysis did not conflict. Therefore, EPA selected the Altman’s Z ́

analysis as the primary analysis for use in determining impacts on the firms in the analysis. 

A.3 Preparing the Post-Compliance Analyses

At this point in the model development, EPA incorporated compliance cost information for the surveyed 

and modeled facilities and firms in all locations analyzed and investigated the impacts on those entities 

under two scenarios. In Scenario 1, EPA assumed that compliance is achieved by screening and 

transporting wastes in an appropriate vessel for offshore disposal. Scenario 2b also presumes screening;

however, EPA assumes the wastes are collected for secondary recovery at cooperative facilities or 

facilities providing access to by-product recovery to others. Costs included capital and installation costs 

and operating and maintenance costs. For certain facilities, but not all, revenues from the recovered 

fishmeal and oil were estimated under Scenario 2b. 16

To create the costs needed to calculate the post-compliance DCF, EPA used its standard Modified 

Accelerated Cost Recovery System (MACRS) model, which EPA has used in numerous ELG analyses for 

final rules (see U.S. EPA, 2000, for a detailed discussion of this model). This model computes pre-tax and 

post-tax PVs, along with tax shields on the cash outlay, and an annualized discounted cash outflow over 

the full period of the analysis for the compliance costs. It uses data on marginal tax rates determined from 

financial reports to calculate tax shields and post-tax outlays. Outputs from this model are used as input to 

the facility closure and firm failure models, through various adjustments that depend on which model is 

being addressed.

A.3.1 Post-Compliance Analysis for Facilities

To measure the impact of compliance costs on facilities, EPA subtracted the PV of DCF for the 

compliance costs calculated by the MACRS model post-tax from the PV of DCF in the baseline. EPA 

also aggregated the outputs to produce a cost of the ELG to all affected entities. Additionally, the outputs 

can be used to create a cost per ton per facility or a cost per ton per processing location. See Attachment 1 

for more information on the outputs provided by the MACRS model.

For facilities excluding firm-facilities, EPA subtracted the post-tax PV of DCF of compliance costs from 

the baseline PV of DCF at each facility with a positive DCF to compute the post-compliance PV of DCF 

at the facility level. If DCF is still positive post-compliance, EPA then compared this number to the 

baseline DCF and calculated a percent change in DCF. Any facility for which DCF is positive in the 

baseline, but negative post-compliance, is considered a facility closure in the post-compliance analysis. 

 16 The engineering cost estimates were 2010 costs, although the DCFs were calculated in 2009 dollars. The 

difference in cost years should not have an impact on outcome. Had DCFs been calculated in 2010 dollars, the 

effects on cash flow post-compliance might have been shown to be slightly less than that calculated.
Cost and Economic Impact Analysis for Alaska Seafood Processors

22

The percent change in DCF is evaluated in the context of the potential effect on a facility’s ability to 

afford some capital replacement in the future, but no “bright line” percentage change is put forth as a 

percentage above which impacts would occur.

A.3.2 Computation of Change in Altman’s Z ́ Inputs for Firms

To measure the impact of compliance costs on firms, the change in the financial situation at the firms as a 

result of incurring the costs of compliance must be estimated. This requires computing the change in 

Altman’s Z ́ inputs using the applicable costs to all facilities owned by a firm. First, the costs for all 

facilities in the petitioning locations are summed and the financial situation at each firm is adjusted to 

account for the change in key line items used to compute the Altman’s Z ́ score. Later, EPA summed the 

costs for all facilities owned in either the petitioning locations or in Kenai Seward or Sitka. To develop 

the post-compliance financial state, EPA used the sum of capital costs to adjust assets upwards and 

liabilities downwards, using a simplifying assumption that the cost is covered by borrowed monies. EPA

also adjusted EBIT by the annualized sum of depreciation and O&M costs as calculated by the cost 

annualization model (see Attachment 1 for more information). Only the 2009 finances are adjusted in the 

post-compliance analysis because the Altman’s Z ́ analysis is usually performed on the most recent year 

of data to predict financial stability going forward. EPA then determined what changes occurred in the 

status of the firms; for example, did any healthy firms fall into the marginal range and did any firms fall 

into the “failure” category. EPA also looked at the percent change in Altman’s Z ́ scores for additional 

information on the magnitude of scoring changes. DCF at the firm level was adjusted in the same manner 

as for DCF at the facility level after the PVs of DCF for compliance costs were aggregated across all 

affected facilities owned by each firm.

Impacts on a firm were assessed if a firm’s Z ́ score that was judged healthy or indeterminate in the 

baseline was calculated to be in the range associated with bankruptcy post-compliance. Such firms would 

be counted as firm failures post-compliance. EPA also noted where a firm in the healthy range moves to 

an indeterminate range, but this is not counted as a firm failure. The percent change in Z ́ scores was used 

only as a means for understanding the magnitude of the change on the firm caused by compliance costs. 

A.4. Other Analyses

Four additional analyses are discussed in this section. The first is a small business analysis. The second is 

a barriers-to-entry analysis, which investigates whether new facilities in the petitioning locations or the 

locations of interest, could meet the requirements, or whether those requirements might discourage the 

establishment of new firms or facilities in these regions. The third analysis is an alternative method of 

determining whether post-compliance cash flows would adequately cover capital replacement. The fourth 

analysis investigates the post-tax annualized costs per ton of waste generated to identify any unusually 

high costs for facilities or locations. (U.S. EPA 2011a)

A.4.1 Small Business Analysis

All but three firms in the analysis are considered small by Small Business Administration definitions,

with fewer than 500 employees, or were presumed small for lack of information. Average employment, 

rather than peak employment, was considered the defining employment figure because of the significant 

seasonality of employment in the industry. The three firms identified as large based on public information

are Trident, Icicle, and Ocean Beauty (see U.S EPA, 2013a). For the small business analysis, EPA

investigated the annualized costs as a percentage of revenues, using the annualized post-tax costs 

estimated for Scenarios 1 and 2b. As has been done in small business analyses previously (see U.S. EPA, 

2000, for example), EPA calculated the annualized costs as a percentage of revenues and reported the 

number of small firms where costs exceeded revenues by one percent and three percent. If no small firms 

experience costs exceeding one percent of revenues, no impacts on small firms are assessed. Specific 
Cost and Economic Impact Analysis for Alaska Seafood Processors

23

results are presented in the reference: Final Costs and Impact Analysis for Alaska Seafood Processors 

(Facilities and Firms) (CBI). (U.S. EPA 2011a)

A.4.2 Barriers to Entry

If no impacts on existing facilities and firms are estimated, EPA usually concludes that no impacts on new 

facilities and firms will occur and, thus, no barriers to entry will be experienced. The barriers-to-entry 

analysis was performed after EPA determined that there would be no facility closures or firm failures as a 

result of meeting the requirements for non-remote facilities in any of the locations analyzed, including the 

locations of interest. New facilities in these areas of Alaska are often existing facilities that are acquired 

and brought back on-line by new or established firms. Thus, these types of “new” facilities can be 

assumed to be reasonably represented by existing facilities. Because all existing facilities are shown to be 

able to afford Scenario 1 costs, newly re-established facilities should also be able to afford these costs. 

In the past, EPA has also used an assessment of whether the capital costs of the additional equipment are 

a substantial portion of the costs to construct a new facility (see, e.g., U.S. EPA, 2006) to determine 

whether barriers to entry exist. If the capital cost for the additional equipment is a small portion of the 

usual engineering contingencies built into construction estimates, EPA has indicated that the cost of a rule 

poses no barriers to entry. It is difficult to estimate what a wholly new facility would cost; however, EPA 

was able to estimate this cost using survey data and an approach outlined in the CBI version of this report 

(U.S. EPA 2011a). The specifics of the approach cannot be detailed to protect confidential business 

information, but are presented in that document. EPA then looked at the capital costs as a percentage of 

the estimated construction costs and compared this percentage to typical engineering contingencies. 

Engineering contingency costs are often 15 to 20 percent of total construction costs. Therefore, if the cost

to add this equipment was only a very small portion of engineering contingency costs, and considering 

that the cost to design in equipment during construction is usually less expensive than the cost to retrofit 

it, the barrier to entry to new seafood processing locations in any of the locations investigated also would 

be considered very small and would be incremental to any existing barriers to entry. Specific results are 

presented in the reference: Final Costs and Impact Analysis for Alaska Seafood Processors (Facilities and 

Firms) (CBI). (U.S. EPA 2011a)

A.4.3 Assessment of Differences in Average Compliance Costs per Ton of Waste 

Generated in Each Location

EPA then compared the costs using tons of waste removed in both the petitioning locations and the 

additional locations of interest. See Table 1 and Table 3 in the body of this document. To do this, EPA

looked at the average costs per ton of waste removed, both including and excluding costs and tons of 

waste removed at locations already known to be using by-product recovery for most of their wastes. This 

is because EPA estimated compliance costs to be lower at the locations where little waste is currently 

being discharged under either scenario. These average costs by location and by scenario were compiled to 

allow EPA to determine whether any locations that incurred, on average, relatively higher costs of 

compliance and to make a determination whether the differences in cost per ton of waste generated seen 

were unacceptably greater than for other locations. The costs per ton also allow EPA to compare them to 

similar costs for other industry categories for which ELGs were previously promulgated by EPA. Specific 

results are presented in the reference: Final Costs and Impact Analysis for Alaska Seafood Processors 

(Facilities and Firms) (CBI). (U.S. EPA 2011a)

A.4.4 Sensitivity Analysis for Capital Replacement

EPA also performed an alternative method for estimating capital replacement costs at single-facility firms 

where facility assets are known.17 In this analysis, capital replacement costs were set at 10 percent of 

 17 Including certain firms treated as single-facility firms.
Cost and Economic Impact Analysis for Alaska Seafood Processors

24

firm-level assets as reported in the Section 308 survey for the single-facility firms. While the results were 

not vastly different, but EPA does not consider that the capital replacement estimate generated this way is 

a satisfactory approach. Firms with newer facilities would tend to have higher assets and a lower 

immediate capital replacement need, and firms with older facilities and fully depreciated assets would 

likely have higher capital replacement needs. EPA chose not to use this method for estimating baseline 

cash flows, although the analysis showed little difference in results. Specific results are presented in the 

reference: Final Costs and Impact Analysis for Alaska Seafood Processors (Facilities and Firms) (CBI)

(U.S. EPA, 2011a).