# 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 Faciliti es 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 Al ternative 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 L ocations: 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 c osts per pound of waste removed

, and economic impact analyses

, for direct discharging Alaska Seafood Processing Industry firms and facilities associated with the petitioning location s 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 locatio n ( 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

. See Report of Quality Activities Supporting Alaska Seafood Processing Cost Estimates (EPA 2013b). Only Scenario 1 is consid ered a basis for the regulatory requirements

. Scenario 2b is discussed as a disc retionary 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 location s, currently classified as remote

. EPA is consider ing reclassifying these location s 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 insta lled 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 d a ta underlying the economic impact an alysis ha s 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. Modele d 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 su mmary 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 Kena i 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 capi tal 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 Co st 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 anal ysis. Sitka is a separate processing location.

## Cost and Economic Impact Analysis for Alaska Seafood Processors

2 

### 1.1 **Summary: Petitioning**  **Location s**  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 b y the costs. 3. Given that the costs for Scenario 1 on a facility basis are $0.02 to $0.04 per pound 

### remov ed. 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 location s can afford t he non

- remote promulgated ELGs u nder 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 location s 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

- r emote 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**  **Peninsu la**  **and Sitka)**
EPA estimates that t he impacts on the firms and facilities in the non

- petitioning location s , 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 d isposal ) . 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 be cause 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 a ny 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 a nd 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 Location**  **s**

Section 2 discusses the annualized costs to the surveyed and modeled facilities in the petitioning location s and provides the total costs to all facilities in the petitioning location s (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 analy ses discussed below in detail.



### 2.1 **Annualized Cos t**  **s to Facilities in the Petitioning Location**  **s** This section presents the annualized costs for the petitioning location s in 2010 dollars. 2 EPA identified a total of 14 facilities operating in these petition citie s. Three of these facilities were not surveyed, but EPA was able to analyze two of them qua l it at ively 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 appropriate 3 . 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 qu estionnaire 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 annualiz ed 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 ana lyses, 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 C BI. 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 rem oved) 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, c ash 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 stand ard 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 . Ra ther, 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 ra w 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 repor ted 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 Pr ocessing Locations Included in Petition 1

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 processi ng 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 t hree canneries in one location are already using by

product 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 includ e 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. Th ese 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 anal ysis. 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. Differe nces 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 Sur vey 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 location s to meet the non

remote wastewater control requir ements under the two scenarios

. T he costs are annualized in this anal ysis using the sur vey

- reported, nominal interest rates, adjusted by a presumed future inflation rate of two percent to create an estimated real discount rate

. Where an in terest 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 cooper ation and sufficient existing by

product recovery located nearby are true under Scenario 2b . However, this is not necessarily true on a facility

- by

- fa cility basis or for all processing location s

. 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 re covery 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 cost s, 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 Location**  **s**

**2.2.1 Baseline Analysis**  Before EPA could determine the financial impacts on facili ties in the petitioning location s , 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 ana lyzed 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 viabil ity 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 Revenu e

– Total Facility Costs + Depreciation” in each year as a proxy for cash flow as reported in the Section 308 survey
responses . E ssentially, this is earnings before interest, taxes, depreciation, and amortization (EBI TDA)

. For single

- facility firms, howeve r, where interest payments could be included in the facility

- level analysis, total facility co sts 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 bet ter 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 repea ted 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 ( us ed in this analysis to represent 2010 doll ars) through the producer price index (PPI) for seafood processors ( B ureau of L abor S tatistics , 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 in flation 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 ann ualized to provide an estimate of the average annual ca sh 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 hav e 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 pr oviding 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 ca ptured 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 explore s another method for estimatin g capital replacement that was not considered useful.

Generally, under Scenario 1, EPA determined that annualized costs are a relatively small portio n of total annualized cash flow; therefore, the cash flow remaining should be adequate to continue to pro vide 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 rep lacement. 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 a utomated 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 f acility might make, a relatively small buffer for capital replacement is estimated to be needed, and EPA conclude s 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 consider s 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 Location**  **s** This section first discusses the overall impacts on firms owning facilities in the petitioning location s in Section 2.3.1. Section 2.3.2 then discusses the impacts to small firms (as defined b y the Small Business Administration [SBA]) relative to those at large firms ( C ode of F ederal R egulations , 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 fir ms 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 location s a re 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 analysi s 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 defin e 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 stren gth, 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 indus try 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 improv ements 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 o r, 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 re liability

. 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 Asse ts

where EBIT is Earnings Before Interest and Taxes 6

A Z ́

- Score greater than 2.9 is considered healthy; between 1.23 and 2.9 is co nsidered indeterminate; and t less than 1.23 is considered to represent distress, with the fi rm considered likely to fail. E PA interpret s 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 Ana lysis for Industrial Laundries (U.S. EPA, 2000) ).

EPA also investigated cash flows to add to the understanding of financial health. EPA calculated firm

level 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 ca sh flow analysis . These included

re spondent

- provided interest rate adjusted for inflation or the seven percent discount rate, and firm

provided financial data inflated to 2009 dollars using the PPI for seafood processors

. Certain other faci lity

- 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 indic ative of future performance

. Because many firms did not provide enough information to deduce income taxes, all cash flows are computed pre

tax

. All firms hav e positive discounted cash flow and so no firms are considered to be baseline failures

. The discoun ted 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 location s 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 adjust ed 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 mos t of these firms.

Given the impacts seen at most of the firms in this analysis, EPA tentatively consider ed 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 a nd 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 general ly 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 th e 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 facil ities in the non

petitioning 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 wh ether facilities and firms in the non

- petitioning location s of interest could afford to meet non

- remote wastewater control requirements, EPA ran the same analyses as described above for petition ing 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 l ocation 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 facilitie s 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 Loc ations of Interest**  EPA surveyed four facilities in these additional locations of interest and was able to quantitatively analyze costs for six non

- surveyed facilities 

### us ing cost estimates developed from the processing facility most closely resembling the f acility being modeled (e.g., size based on total production, etc.)

.

Table 3 presents the results of the cost annualization ( U.S. EPA 201 3 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 location s of interest. This is true because a facility has been proposed (S itka 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 v e ssel

. However, it is true that, generally, costs under Scenario 2b for facilities in t he 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 by

product 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 Locations 1

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 an d individual by

- product recovery in place and thus comply with effluent limitations based upon screening. Three additional
proce ssors 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 failure s.

The cost per ton for the additional locations of interest is margin ally 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 th e 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. None theless, EPA estimates t hese 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 re ductions 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 location s 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 Scenar io 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 Alt man’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 perc ent . 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 i n the petitioning location s are not expected to experience closures or fir m failures under Scenario 1, EPA extend ed the analysis, qualitatively, to the two facilities and four firms not analyzed quantitatively . EPA tentatively consider ed 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. Moreo ver, 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 facilit ies in the petitioning location s 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 for e going analyses have shown that existing facilities and firms can afford the basic requirements
represe nted 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, 200 6 ). 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 rul e 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 facilitie s

## Cost and Economic Impact Analysis for Alaska Seafood Processors

12 in any of the location s 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 estimati ng 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 outc ome of the analysis. However, EPA do es 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 replaceme nt 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 th e 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 S hips 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 Poll utant Discharge Elim i nation 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 L ocations 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, 201 3a . Profile of the Alaska Seafood Processing Industry

. August

. (DCN 00412)

U.S. EPA, 201 3 b

. Report of Quality Activities Supporting Alaska Seafood Processing Cost Estimates, Augu st

. (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 location s. 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 location s.

• 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 foll owing 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 location s a nd their six firms that are currently discharging their wastewater in the petitioning location s. 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 discu sses a preliminary step to identify appropriate models for the facilities and firms in the petitioning location s 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 meth ods 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 facil ities and firms i n two other location s 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 location s and the two analyzed location s of interest

.

9 No discharging facilities currently are located in Anchorage, however; facilities and their firm s 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

- extra cted the key financial data from the Section 308 survey questionnaire data submitted by the firms and their facilities that were located in the petitioning location s to develop a preliminary baseline analysis of facilities and to test possible approaches f or 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 location s prior to receiving electronic survey data because of the li mited 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 tha t were not surveyed. The Section 308 survey provided information on 11 of the 14 discharging facilities in the petitioning location s

. 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 nin e firms owning facilities in the petitioning location s where discharge is still occurrin g. These similarities were assessed using information from NPDES reports and other data (U.S. EPA, 201 3a
, 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 201 3 1 a, 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 w as surveyed. The four non

- surveyed facilities in the Kenai Peninsula resemble

ano the r 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 location s ( U. S. EPA 201 3a, b). Another processor in Sitka is much larger in terms of quantities of seafood processed than any facility processing only fresh and frozen sea food . T hus, it is not assigned model facility financials and is analyzed qua l itatively. 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 analyse s 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 analys e s of effluent guidelines (see, e.g., U.S EPA, 2002 ). In DC F 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

. Th e cash flow is approximated, typically, by using total revenues minus total costs, and adding back in depreciatio n, because depreciation is a non

- cash item in the total costs line item. Cash flow is considered by most financial analysts as a key determinan t 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 O perating 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, i nterest, 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 o n depreciation that could be used to adjust total outlays to a cash flow approximation. T he se profit centers, where a full income statement was available at least thro ugh earnings before taxes [EBT], were analyzed using EBT plus depreciation as a proxy fo r cash flow (EBTDA)

. Additiona lly, 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 Fac ility 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 fina ncial 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, 2 010). Because the Alaska seafood processing industry is a major contributor to the U.S. economy within this sector (see U.S. EPA, 201 3a ), EPA considered the PPI for this industry as the best inflator to use. These earnings/cash flow were then extended out 1 0 years; i.e., under an assumption that the last five years of financial data are reasonably repr esentative of the next 10
years, and discounted using either seven percent or the owner firm’s reported current interest rate after conversion to a rea l rate. EPA evaluated t rends following cal culation of each facility’s DCF ( see below).

EPA needed to address a few data gaps p rior 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 f acility costs for another facility for 2005 and 2006 , which were assumed identical to th ose in 2007 for reasons that are CBI ( see U.S. EPA , 2011 a ). These data imputations allowed EPA to use the same projection method for these two facilities used for the o thers. 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 disco unt rate for all facilit ies i n the preliminary analysis for simplicity (OMB, 2003).

11 S everal 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 disco unted 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 facili ty is considered a cost center, even if reporting EBT. If this occurred

, EPA would not anal yze 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 incl ude whether any trends mi ght 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 all ow firms to maintain t heir 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 qu estionnaire reported interest rates

, and tied the facility analysis to the firm

- level analysis . T his 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 an nual 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 ava ilable in most cases, EPA believe s that the data captured provide a reasonable representation of the relatively unpredictable boom and bust cycles common to the industry (see EPA , 201 3a ). 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 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

. EPA r ecently has looke d at capital replacemen t costs, which are costs beyond those captur ed 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 capita l replacement. Such expenditure is not a cost incurred to allow the firm to continue as it is, but t o 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 pro vides a sense of the impact on cash flow fr om the two scenarios analyzed. EPA also provide s 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 efficien t 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 a re 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 re flected 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 du e 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 f irm

- level analysis is discussed below. First, EPA review s 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 possib le 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,” b ut 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 avail able in financial reports and, presumably, in the surveys.

13 B ecause seafood processing is considered a manufacturing industry, EPA considered it possible to assess firm

level 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 mod erate 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 a nd 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 replaceme nt 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 i ndicates “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 processi ng 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 be lieved 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 fin ancial 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 hel d 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 hel d; 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 Li abilities)/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 Taxes 15

.

A Z ́ Score greater than 2.9 is considered healthy, between 1.23 and 2.9 is considered indeterminate, and l ower than 1.23 is considered to represent distress, with the firm considered likely to fail

. EPA interpret s a baseline score above failing as a non

- failing firm in this analysis, which is the same appr oach used in other effluent guidelines analyses (see, e.g., the Economic Ana lysis for Industrial Laundries ( U.S. EPA, 2000 ) ).

Because of indeterminate Z ́ scores, which EPA consider s likely to represent a “marginal” condition, EPA also investigated cash fl ows 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 facil ity

- 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 . F or one firm in 2005 an d 2006 that did not provide data for those two years, EPA filled those years with data from 2007 . A l l 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 sol ely 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’ per formance

. 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 location s 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 fo r offshore disposal . Scenario 2b also presumes screening ; however, EPA assumes the wastes are collected for secondary recovery at cooperative facilities or fa cilities providing access to by

- product recovery to others. Costs included capital and installatio n costs and operating and maintenanc e 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 Modif ied 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 PV s, 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 t he outputs to produce a cost of the ELG to all affected entities. Additionally, the outputs can be used to cre ate 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 cost s 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 i n 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 calc ulated 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 abi lity 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 cost s 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 location s 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

. L ater, EPA summed the costs for all facilities own ed in either the petitioning location s or in Kenai Seward or Sitka. To develop the post

- compliance financial state, EPA used the sum of capital costs to adjust assets upw ards and liabilities downwards, using a simplifying assumption that the cos t is covere d 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 th e 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 occur red in the status of the firms; for example , did any healthy firms fall into the margi nal 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 th e facility level after the PV s 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 b e 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 percen t 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 se cond is a barriers

- to

- entry analysis, which investigates whether new facilit ies in the petitioning location s or the location s of interest, could meet the requirements, or whether those requirements might discourage the establishment of new firms or facilit ies 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 ide ntify any unusually high costs for facilities or location s



### . (U.S. EPA 2011a)

**A**

**. 4.1**  **Small Business Analysis** All but three firms in the analysis are considered small by Small Busin ess 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 , 201 3a )

. For the small business analysis, EPA investigated the annualized costs as a percentage of revenues, using the annualized post

- tax costs estimated for Scenario s 1 and 2b. As has been d one 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 experience d

. The barriers

- to

- entry analysis was perfo rmed 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 location s analyzed

, in cluding the location s of interest . New facilities in these areas of Alaska are often existing facilities that a re 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 equip ment 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 2011 a ). The specifics of the approach cannot be detailed to protect confidential business information, but are presented in that document. EPA the n 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 constructio n costs. Therefore, if the cos t 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 pro cessing location s in any of the location s 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 Lo**  **cation**
EPA then compared the costs using tons of waste remov ed in both the petitioning location s and the additional location s 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 re mov ed

, both including and excluding costs and tons of
waste remov ed at location s already known to be using by

- product re covery for most of their wastes. This is because EPA estimated compliance costs to be lower at the location s where little waste is curre ntly being d ischarged under either scenario . These average costs by location and by scenario were compiled to allow EPA to determine whether any location s that incurred, on average, relatively higher costs of complianc e and to make a determination whether the differences in cost per ton of waste generated seen

were unacceptably greater than for other location s

. 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 e stimating 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 certa in 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. Whil e the r esults were not vastly different, but EPA do es not consider that the capital replacement estimate generated this way is a satisfactory approach . F irms 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, 2011 a ).