Northeast Trip Cost Data - Overview, 

Estimation, and Predictions 

Chhandita Das 

NOAA Fisheries, Northeast Fisheries Science Center/Integrated Statistics, 

13 Church Street, Woods Hole, MA 02543 

US DEPARTMENT OF COMMERCE 

National Oceanic and Atmospheric Administration 

National Marine Fisheries Service 

Northeast Fisheries Science Center 

Woods Hole, Massachusetts 

November 2013

NOAA Technical Memorandum NMFS-NE-227 
Northeast Trip Cost Data - Overview, 

Estimation, and Predictions 

Chhandita Das 

NOAA Fisheries, Northeast Fisheries Science Center/Integrated Statistics, 

13 Church Street, Woods Hole, MA 02543 

 

US DEPARTMENT OF COMMERCE 

Penny Pritzker, Secretary 

National Oceanic and Atmospheric Administration 

Kathryn Sullivan, Acting NOAA Administrator 

National Marine Fisheries Service 

Samuel D. Rauch III, Acting Assistant Administrator for Fisheries 

Northeast Fisheries Science Center 

Woods Hole, Massachusetts 

November 2013

NOAA Technical Memorandum NMFS-NE-227 

This series represents a secondary level of scientific publishing. All issues employ thorough internal 

scientific review; some issues employ external scientific review. Reviews are transparent collegial 

reviews, not anonymous peer reviews. All issues may be cited in formal scientific communications. 
Editorial Notes 

Information Quality Act Compliance: In accordance with section 515 of Public Law 106-554, the 

Northeast Fisheries Science Center completed both technical and policy reviews for this report. 

These predissemination reviews are on file at the NEFSC Editorial Office. 

Species Names: The NEFSC Editorial Office’s policy on the use of species names in all 

technical communications is generally to follow the American Fisheries Society’s lists of 

scientific and common names for fishes, mollusks, and decapod crustaceans and to follow the 

Society for Marine Mammalogy's guidance on scientific and common names for marine 

mammals. Exceptions to this policy occur when there are subsequent compelling revisions in the 

classifications of species, resulting in changes in the names of species. 

Statistical Terms: The NEFSC Editorial Office’s policy on the use of statistical terms in all 

technical communications is generally to follow the International Standards Organization’s 

handbook of statistical methods. 

Internet Availability: This issue of the NOAA Technical Memorandum NMFS-NE series is 

being as a paper and Web document in HTML (and thus searchable) and PDF formats and can be 

accessed at: http://www.nefsc.noaa.gov/nefsc/publications/. 
ii 

TABLE OF CONTENTS 

Executive Summary ........................................................................................................................ 1 

1 Introduction ................................................................................................................................. 1 

2 Data Collection Methodology ..................................................................................................... 1 

2.1 Coverage............................................................................................................................... 2 

2.1.1 Length Categories .......................................................................................................... 2 

2.1.2 Principal Gear Groups ................................................................................................... 3 

2.1.3 Principal Species Groups ............................................................................................... 3 

3 Data Overview ............................................................................................................................ 3 

3.1 Data Quality Assessment ..................................................................................................... 4 

3.2 Data Summary ...................................................................................................................... 4 

4 Estimation and Prediction ........................................................................................................... 5 

4.1 Estimation - the Modeling Framework ................................................................................ 5 

4.1.1 Estimates ........................................................................................................................ 6 

4.2 Prediction ............................................................................................................................. 7 

5 Concluding Remarks ................................................................................................................... 8 

Acknowledgements ......................................................................................................................... 8 

References Cited ............................................................................................................................. 9

LIST OF TABLES 

Table 1. Number of trips and vessels observed 2005-2012. ......................................................... 10 

Table 2. Frequency of unique number of vessels observed. ......................................................... 10 

Table 3. Frequency and percentage of trips observed by length categories and by year. ............. 10 

Table 4. Frequency and percentage of trips observed by principal gear groups and by year. ...... 11 

Table 5. Frequency and percentage of trips observed by principal species groups and by year, 

continued. ...................................................................................................................................... 11 

Table 6. Frequency and percentage of trips observed by principal species groups and by year. . 12 

Table 7. Summary statistics of individual cost items over the analysis period (2008-2012). ...... 12 

Table 8. Summary statistics of total costs at different levels of aggregations. ............................. 12 

Table 9. Summary Statistics of total cost by trip duration types and by length categories. ......... 12 

Table 10. Summary statistics of total cost of different trip types by gear categories. .................. 13 

Table 11. Summary statistics of the continuous variables considered in model estimation. ........ 13 

Table 12. Frequency distribution of the discrete variables considered in model estimation. ....... 14 

Table 13. Generalized Linear Model (GLM) parameter estimates using all observed trips. ........ 14 

Table 14. Summary statistics of the continuous variables considered in the prediction data. ...... 15 

Table 15. Frequency distribution of the discrete variables in prediction data. ............................. 15 

Table 16. Total trips costs observed and predicted. ...................................................................... 16 

Table 17. Observed and predicted cost summaries by trip duration types and vessel length 

categories. ..................................................................................................................................... 16 

Table 18. Summary statistics of observed and predicted costs by principal gear types. .............. 16
iii 

LIST OF FIGURES 

Figure 1. Total cost distributions by trip duration types and vessel length categories. ................ 17 

Figure 2. Total cost distributions by vessels’ principal gear groups. ............................................ 18 

Figure 3. Histogram of the total cost distribution. ........................................................................ 19

Figure 4. Distributions of predicted costs by trip duration types and vessel length categories. ... 20 
1 

EXECUTIVE SUMMARY 

Fisheries trip cost data are needed to accurately assess the economic impacts proposed 

management regulations. These data serve as input in a variety of analyses conducted by the 

Social Sciences Branch (SSB) at the Northeast Fisheries Science Center. Lack of these data 

would create constraints on the type of economic analysis that SSB economists can provide to 

fisheries decision-makers in the New England Fishery Management Council, the Mid-Atlantic 

Fishery Management Council, and National Marine Fisheries Service (NMFS), on behalf of the 

Secretary of Commerce, to help them make informed management decisions. 

This document gives an overview of the latest eight years of trip cost data, from 2005-

2012. It explains the data collection process, types of data collected, and data coverage and 

quality. Several summary statistics of the data by selected vessel and trip characteristics are also 

presented. A modeling framework for estimation and prediction of costs is also given. This 

process will allow estimation of vessel level aggregate trip cost, which in combination with a 

vessel’s annual cost can give an overall fisheries cost assessment. This analysis is expected to 

improve the capacity of the SSB in conducting more comprehensive research and analysis. 

1 INTRODUCTION 

Economic data about the costs of operating commercial fishing businesses are used in 

many analyses required for frameworks and amendments related to fisheries management plans. 

Examples include regulatory flexibility analyses and economic impact assessments for proposed 

regulatory actions. These analyses are needed by the National Marine Fisheries Service (NMFS) 

to meet the legislative requirements of the Magnuson-Stevens Fishery Conservation and 

Management Act, the National Environmental Policy Act, Executive Order 12866, and the 

Regulatory Flexibility Act. Beyond that, these economic data also serve as input for other 

analyses, such as estimating economic profitability profiles, fleet efficiency, and productivity 

indices. The Social Sciences Branch (SSB) of the Northeast Fisheries Science Center is primarily 

responsible for conducting these analyses, which would be incomplete without an accurate 

understanding of the financial costs faced by commercial fishing businesses. 

Commercial fishing vessels typically incur two major types of costs: annual costs and trip 

costs. Annual costs include all those costs which fishing vessel owners bear irrespective of 

whether they take a fishing trip or not. Trip costs are those costs which are typically incurred 

during a fishing trip. This document focuses on fishing vessels’ trip related cost data. Section II 

discusses the data collection methodology; section III discusses the types of trip cost data 

collected and provides summary statistics of these data. An econometric modeling framework for 

estimation and predictions of trip costs is presented in section IV. Finally, section V concludes 

this discussion. 

2 DATA COLLECTION METHODOLOGY 

In the Northeast, the trip costs data are collected as a part of the Northeast Fishery 

Observer Program’s (NEFOP) data collection effort. The Fisheries Sampling Branch oversees 

the NEFOP, which collects, processes, and manages the data obtained during commercial fishing 

trips. Biological and economic data are collected by trained personal (officially known as 

observers) for scientific and management purposes. The economic data are obtained either via 

personal observation or by interviewing the captain. 
2 

Although, the NEFOP has been collecting trip related cost data since 1989, this study 

focuses only on the past eight years, from 2005-2012. An overview of the observer program 

coverage during the study period is presented in the following section. This analysis helps us 

understand the types of vessels and trips typically covered by the NEFOP. 

2.1 Coverage 

The observer program coverage was assessed by evaluating annual changes in the 

percentages of total number of commercial trips and vessels observed each year. Vessel log 

reports were used to calculate the total number of trips taken during a year, and the observer data 

were used to calculate frequencies of observed trips. Based on the vessel log report, 908,172 

commercial fishing trips took place during the study period, 2005-2012.1 Table 1 shows overall 

number of vessels and trips and the number observed by year. The table shows that on average, 

41% of the vessels and 3.60% of trips were observed each year. However, since the same vessels 

could be observed in multiple years, Table 2 shows the number of unique vessels that were 

observed during this study period. The data show that 1,999 unique vessels were observed during 

the study period. Out of these, 191 vessels were observed in all years from 2005- 2012, and 

1,289 vessels were observed more than once but not every year. Only 519 vessels were observed 

in just a single year during this time period. 

Next, the coverage was further explored by calculating the percentage of trips observed 

by vessel length, principal gear, and species for each trip. Principal gear and species for each trip 

were identified by the gear and species that accounted for the maximum share of the revenue for 

that trip. Principal variables for the universe of trips were calculated by using vessel logbook 

data and dealer data (for species prices). The principal variables for the observed trips were 

calculated by using the observer data.2 The vessels’ physical characteristics were calculated 

using permit data. These results are shown from Table 3 to Table 6. 

2.1.1 Length Categories 

Table 3 shows the frequencies and percentages of trips observed by vessel length 

categories. For this analysis, the vessels were grouped into three size categories, Large, Medium, 

and Small. Vessels longer than 80 ft were labeled as Large vessels between 40 ft to 80 ft were 

labeled as Medium, and vessels smaller than 40 ft were labeled as Small. Unclassified category 

included vessels that had missing information on length in the permit database. 

Table 3 shows the majority of the trips were accounted for by the Medium size vessels, 

followed by the Small and Large vessels. However, the percentage coverage by the observer 

program was highest for the Large vessels. On average, the percentage of observed trips for the 

Small vessels were about 2%, for Medium vessels about 4%, and about 10% for the Large 

vessels. The coverage percentages steadily increased over the years for Large and Medium

vessels, with the exception of a slight decline in the observed trips in 2006. 

 

1

 Recreational trips were identified based on trip category values in the vessel trip records and were not included in 

this analysis. 

2

 For calculating aggregate landing and revenue per trip, only valid landings were considered excluding the 

discarded landings, as noted in the observer data. 
3 

2.1.2 Principal Gear Groups 

The observer coverage by principal gear groups is discussed in Table 4. Principal gear for 

each trip was identified by the gear with the maximum revenue share for that trip. Then these 

gears were mapped into eight different gear groups: Dredge, Gillnet, Handgear, Longline, 

Midwater Pair Trawl, Midwater Trawl, Pot/Trap, and Trawl. All principal gears not included in 

the eight groups mentioned earlier, were grouped under Others gear group. There were also 

several trips where nothing was caught that were labeled separately as No Catch. Table 4 shows 

the trip frequencies by principal gear group along with the numbers and percentages of trips 

observed for each gear group. 

Table 4 shows that the majority of the trips primarily used Gillnet, Pot/Trap, or Trawl in 

every year from 2005-2012. However, the observer coverage for Pot/Trap remained close to 0% 

in all years. The percentage coverage for all other gear groups have increased over time with 

occasional fluctuations. Coverage for Midwater Pair Trawl and Midwater Trawl have 

substantially increased in recent years, amounting to over 40%. This is because of the increased 

effort by the NEFOP to observe the groundfish vessels which primarily use trawl gears. 

2.1.3 Principal Species Groups 

Principal species were determined by the maximum revenue share for each trip. These 

species were then mapped into fifteen groups. Species were grouped based on their common 

names, commercial importance, and common management rules. For example, the Groundfish 

Large Mesh group includes cod, flounder, haddock, white hake, halibut, pollock, redfish, and 

wolffish. Groundfish Small Mesh includes red hake, silver hake, and ocean pout. Midatlantic 

Mixed Trawl includes black sea bass, fluke, and scup. Trips with no catches were grouped under 

No Catch species group. The trip frequencies by the principal species groups are shown in Table 

5 and Table 6, along with the number and percentage of trips observed for each group. 

Tables 5 and 6 show that lobster was the principal species group for the majority of the 

trips, followed by either Mid-Atlantic Mixed trawl, ground fish-large mesh, or scallop in this 

eight year study period. The observer coverage for most species was below 10% until 2009. 

Since 2009, coverage of ground fish-large mesh, herring, monkfish, and skate has increased by a 

large percentage. Although, the majority of the trips in all 8 years had lobster as a principal 

species, its observed trips were less than 1%. There has been no coverage for red crab, surf clam 

ocean quahog (SCOQ), and tilefish trips since 2009. 

The analysis shows the observer coverage varies largely within different vessel and trip 

types. Although, the overall coverage percentages for most of trip types are small, the absolute 

numbers of trips covered are often large because of the high number of total trips. Therefore, the 

numbers of observed trips are often sufficient for drawing inferences.3

3 DATA OVERVIEW 

This section elaborates on the trip related costs. The methods for identifying and 

removing data anomalies are also discussed here. Finally, several summary statistics of the cost 

 

3

 Dillman et al.’s (2009, page 57) formula about the sample size needed for population estimates of a given size is 

used as a guidance. 
4 

data are presented. The data analysis was conducted using only the latest 5 years’ of data, i.e. 

2008-2012. All cost values were converted to 2012 dollars for the rest of the analysis.4

 

The observer questionnaire contains eight different cost related questions. The observer 

requests this information from the captain while at sea. These questions are about expenses of 

bait purchased for the trip, damages or losses encountered during the trip, food purchased for 

crew and captain during the trip, lubricating oil, fresh water, and other commonly used supplies 

purchased for the trip. The captain is also asked to provide information on the amount of ice and 

fuel used, and the prices at which ice and fuel were purchased are also recorded. During the 

interview process, it is emphasized that the cost reporting should pertain to the associated trip 

only. If some costs are distributed over trips, the captain is requested to give his best estimate of 

the cost share of the trip in question. 

3.1 Data Quality Assessment 

Before analyzing these cost data, it was necessary to remove any anomalies that may 

exist in the data. Data anomalies were identified by plotting each individual cost item and 

aggregate cost values in a scatter diagram. Costs were also plotted against trip duration and 

vessel length. A cost was considered to be an outlier based on its distance from the mean values 

as well as its position with respect to the rest of the distribution and was subsequently removed 

from summary calculations. Also, several trips had positive total trip costs but had not provided 

any information on fuel cost (fuel usage) for those trips. These trips were also eliminated from 

the analysis as it is expected that a vessel will incur some fuel cost if it has left port for a fishing 

trip. Trips with very low cost values (less than $10) were also eliminated from the summary 

calculations. This process led to an elimination of 2% of the total observations. 

3.2 Data Summary 

Table 7 shows the summary statistics of the individual cost items along with their shares 

in total trip costs for the 5 year period under consideration. The ice cost and fuel cost were 

calculated by multiplying the usage of these items with their corresponding prices. Some trips 

had reported fuel (or ice) quantities but reported no corresponding prices; monthly mean prices 

for each year were used to calculate the total fuel (or ice) cost for these trips. 

The average cost is highest for fuel, followed by food and damage. The data show that 

the average expenses of bait, water, supplies, and oil were less than $100. Moreover, bait, 

damages, supplies, and water, all have zero median costs, indicating 50% or more trips had no 

expenses for these items during the study period. An explanation for zero median bait cost is that 

many vessels do not use bait. Also, damage costs are only incurred when vessels suffer some 

damage during a trip, which is possibly not a regular occurrence. Crew members often bring 

their own supplies so these costs do not occur on every trip. Water is often included with docking 

fees, so separate charges for water are not often reported. 

As expected, fuel costs account for the maximum share of total trip costs, averaging 

about 78%. The next highest share is for food costs followed by ice costs and damage costs. 

 

4

 Producer Price Index for unprocessed finfish was used to make these conversions. 
5 

However, the mean shares of total costs for all items, except fuel, are below 10%. Water has the 

lowest share, which is less than 1.00%.5

 

Table 8 shows summary statistics of the total trip costs at different levels of aggregation. 

The table shows that the average trip cost for all observed trips is $4,013 with a standard 

deviation of $7,366. Out of all the trips considered for this analysis, 64% were single day trips 

(trip duration ≤ 24 hours), and 36% were multiday (trip duration >24 hours). The average total 

cost for single day trips is $335, which is about 3.00% of the average costs of the multiday trips 

($10,468). 

The summaries of total trip costs by vessel lengths are reported in Table 9. Average total 

trip cost for small vessels ($279) is lower than the same for medium ($2,750) and large vessels 

($15,819). These cost differences could be a result of the trip characteristics of the small vessels. 

The majority of the trips by small vessels were single day trips (95%) and used gillnets (76%) 

which are typically associated with low average costs. On the other hand, the majority of the 

trips by large vessels was multiday trips (96%) and used either dredge or trawl (75%) which on 

average has a high cost. The graphical representation in Figure 1 shows a higher dispersion in 

costs for larger vessels compared to medium and smaller vessels as well as for multiday trips 

compared to day trips. 

The aggregate cost summaries by gear groups are presented in Table 10. Average 

aggregate costs are highest for Midwater Trawl, Midwater Pair Trawl, and Dredge gear groups 

and lowest for Gillnet, Handgear, and Longline. A similar pattern is observed for the multiday 

trips. For single day trips, Midwater Trawl gear group is associated with large average costs 

compared to the other gears. A graphical representation of the total cost distributions by gear 

groups are shown in Figure 2. 

4 ESTIMATION AND PREDICTION 

Generally, the total number of trips taken by all active commercial vessels in the 

Northeast is about 100,000 in a year. Since the observer program only covers a fraction of these 

trips, trip cost measures are not available for all these trips. However, analysts often need cost 

estimates for trips that were unobserved. The purpose of this analysis is to build sound and 

robust econometric models which can predict costs for all such trips. This section discusses the 

modeling framework for estimation and prediction of trip costs. 

4.1 Estimation - the Modeling Framework 

Typically, an ordinary least square method (OLS) is used to estimate fisheries cost. The 

challenge in using OLS with cost data is that it often leads to negative cost predictions. Therefore 

researchers often use OLS with the log of the dependent variable, and predict cost via 

exponentiating the predicted cost values in log scales. However, this retransformation, though 

often used, causes bias (Manning 1998; Jia and Rathi 2008; Manning and Mullahy 2001). The 

bias is worse if there is heteroscedasticity in the log-transformed model. To correctly predict 

when using the log-transformed linear model estimation, analysts have to apply proper 

adjustments with anti-log-transformation. However, this adjustment process for unbiasedness 

involves calculating a smearing factor which requires several steps, making the process very 

 

5

 Total costs with missing and zero values were not included in these summary statistics calculation. 
6 

labor intensive. Consequently, an alternative method which has gained popularity among 

researchers while dealing with cost data is the generalized linear model (GLM). 

The GLM can be viewed as a differentially weighted, non-linear, least-square estimation. 

The advantages in using GLM are that no adjustment is needed for anti-log transformation and 

GLM does not assume constant variance. GLM is also a preferred method for analyzing skewed 

data as often encountered while analyzing cost or expense data. These data are typically 

characterized by (a) nonnegative measurements of the outcomes and (b) a positively skewed 

empirical distribution of the nonzero realizations (Manning and Mullahy 2001; Moran et al. 

2007). Several examples of GLM application can be found in health economics for analyzing 

health expense data (Knerer et al. 2005; Wu et al. 2007; Moran et al. 2007). Since trip cost data 

are similarly skewed, they were modeled using GLM. The skewness of the cost distributions is 

evident in Figure 3. The estimation was carried out by assuming a gamma distribution for the 

response variable and a log-link function.6

 

Independent variables that could potentially impact a vessel’s trip costs were defined 

based on permit data, vessel log book, and dealer data and are described in Tables 11 and 12.7 To 

account for the year specific impacts, dummy variables for the individual years included in the 

estimation data set were used. The tables show that vessels included in estimation data on 

average were 25 years old and 57 ft long, had horse power of 499, weighed about 69 tons, took 

84 trips on average per year, and earned an annual gross revenue of $555,000. In addition, the 

trips included in the estimation set on average, 52 hours long, had a landed weight of 27,000 lb, 

earned a gross revenue of $40,000, hired 4 crew members, and paid an average price of $3.19 per 

gallon for fuel. Table 12 shows that the majority of the trips were single-day trips (62%), used 

either trawl or gillnet gears as their primary gears (84%), and primarily landed their catches in 

the New England Region (80%). 

4.1.1 Estimates 

The GLM estimates are presented in Table 13. The final model was selected based on 

log-likelihood value, mean absolute error (MAE), and root mean square error value (RMSE). A 

better fit is associated with high log-likelihood value and low MAE and RMSE values. For 

estimation, 19,805 trips were used, which are about 93% of the total valid observed trips. All 

variables included in the final model are significant. The estimates indicate that trip costs are 

higher for larger boats with higher gross tons per feet. As expected, trip cost is highly positively 

correlated with fuel price and trip duration. Consistent with the data summaries, a positive 

coefficient for multiday trip indicator implies trips lasting longer than a day cost significantly 

more than trips lasting 24 hours or less. 

The total number of trips per vessel is used as a predictor to capture the activity factor of 

the vessels. The negative coefficient for this variable indicates vessels taking a large number of 

trips have lower trip costs. This might be because vessels often distribute their costs over trips. 

Therefore, vessels taking large number of trips might be able to reduce their per trip costs by 

economizing on their expenses by, for example, buying in bulk. Total trip revenue has a negative 

 

6

 Other distributions (Inverse Gaussian and Normal) were considered, but Gamma was chosen based on loglikelihood value, AIC and BIC. Also, gamma distribution is frequently used in cost analysis with GLM (Moran et al. 

2007; Knerer et al. 2005). 

7

 Observations with illogical values for the possible independent variables (e.g. tripdur < 0) were deleted from the 

estimation data. 
7 

impact on trip cost, implying trips with high revenues have lower trip costs. Although this result 

may seem counter intuitive, it could be a result of a combination of factors. For example, trips 

could cost less because of shorter duration and low cost gear usage but might be associated with 

higher revenues because of concentrating on higher valued species. Gillnet gear dummy has a 

significant negative coefficient implying lower costs for trips primarily using gillnet gear than 

other types of gears. This result is consistent with the data summary results. Estimates also reveal 

that trip costs were significantly higher in year 2008 compared to the other years considered for 

the model estimation.8

 

4.2 Prediction 

This section discusses predictions for all the trips (observed and unobserved) taken 

during this 5-year period. The independent variables for the predictions data set are described in 

Tables 14 and 15. The tables show that the vessels included in the prediction data set were on 

average 24 years old and 48 feet long, had horse power of 407, weighed 42 tons, took about 94 

trips per year, and earned a revenue of about $313,000. The trips in the prediction data set on 

average were 26 hours long, hired 2 crews, paid on average $3.10 per gallon for fuel, and earned 

a revenue of $8,000 with a landing weight of 6,000 lb. Table 15 shows that the trips in the 

prediction data set were largely single day trips (82%). The data show that 43% trips used 

primarily trawl or gillnet, and about 68% trips landed their catch in the New England region. 

Cost predictions were generated by using the estimates from Table 13, and summaries of 

these predicted costs are presented in Table 16. For comparison purposes, this table also displays 

the known cost summaries for the trips in the estimation set. All dollar values are in 2012 dollars 

for the prediction analyses as well. Similar to the estimation data set, the prediction data excludes 

trips which had illogical values for some independent variables (E.g., negative age calculation 

and extreme values for some independent variables). For summary calculations, extreme cost 

predictions were removed, which were identified via plotting the predicted cost values for all 

trips and also against vessel length. 

The table shows that the average predicted cost is $1,798 with a standard deviation of 

$6,123 for all trips in the prediction set. The low predicted average cost can be explained by the 

fact that the percentage of single day trips in the prediction data set (82%) was higher than the 

estimation data set (62%), whose average cost is substantially lower than the multiday trips. The 

predicted average cost for single day trips is $375 which is comparable to the same for the 

observed average cost ($335). The same results hold for the predicted costs for the multiday trips 

as well. 

Predicted cost summaries by vessel length categories and trip duration are reported in 

Table 17. As noted for the observed trips, the predicted costs were highest for large vessels and 

lowest for the small vessels. The predicted costs for single and multiday trips display a similar 

trend as the observed costs. In comparison to the observed costs, considering all trips, the 

average predicted costs are slightly lower for the medium vessels, and slightly higher for the 

large and small vessels. The highest dispersion in the predicted costs is noted for the large 

vessels on multiday trips (Figure 4). 

Cost predictions by gear groups are presented in Table 18. The highest predicted costs are 

reported for Midwater Trawl and Midwater Pair Trawl, and the lowest predicted costs are 

 

8

 Four dummies to represent each year from 2008 to 2011 were considered but only the significant dummy variables 

were included in the final model. 
8 

estimated for Gillnet and Handgear. These results are consistent with the observed costs. The 

high divergence between the observed and predicted average costs, as recorded for Dredge and 

Pot/Trap, could result from a different composition of trip types in the prediction data set 

compared to the estimation data set. 

5 CONCLUDING REMARKS 

This document explains the Northeast Fisheries Science Center’s effort to collect trip cost 

data as a part of the Northeast Observer Data Collection Program (NEFOP). A comprehensive 

analysis is presented here that considers the most recent eight years (2005- 2012) of data. 

Frequencies of trips taken and percentages of those observed by the NEFOP are presented by 

vessel and trip characteristics. The data collection method and the types of cost data collected are 

also discussed. Several summary statistics and graphical representations are given by vessel and 

trip characteristics. The data were reviewed for possible outliers before conducting this analysis. 

A modeling approach is also discussed to enable cost predictions for trips that were not observed 

by the NEFOP. Summaries of predicted costs based on model-coefficients are presented in 

comparison to observed costs. The predicted costs are consistent with the observed costs in most 

cases. The inconsistencies mostly resulted from the different composition of trips in the 

prediction data set compared to the observed trips data. 

Although this document attempts to give an overview of vessels’ trip costs, it does not 

include all possible costs that a vessel may accrue during a trip. However, a reasonable estimate 

of trip costs can be obtained from this analysis. The trip related costs along with the vessels’ 

annual costs can be combined to give an overall assessment of vessels’ fishing business costs. An 

estimate of net revenues then can be obtained by subtracting these cost values from the gross 

revenue figures. This cost information will improve the capability of the Social Sciences Branch 

to produce analyses that require cost or revenue data such as the estimation of profitability 

profiles and evaluation of the economic impacts of quota changes on Groundfish sectors. 

ACKNOWLEDGEMENTS 

The author thanks Andrew Kitts, Geret DePiper, and Matthew McPherson for their 

comments and suggestions. 
9 

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Dillman DA, Smyth JD, Christian LM. 2009. Internet, mail and mixed-mode surveys: The 

tailored design method. 3rd ed, John Wiley & Sons, Inc. 

Jia S, Rathi S. 2008. On predicting log-transformed linear models with heteroscedasticity. SAS 

Global Forum. P1-6. 

Knerer G, Byford S, Johnson T, Seivewright H, Tyrer P. 2005. The Nottingham study of neurotic 

disorder: Predictors of 12 year costs. Acta Psychiatrica Scandinavica 112(3):224–232. 

Manning WG. 1998. The logged dependent variable, heteroscedasticity, and the retransformation 

problem. Journal of Health Economics 17(3):283–295. 

Manning WG, Mullahy J. 2001. Estimating log models: To transform or not to transform? 

Journal of Health Economics 20(4):461–494. 

Moran JL, Solomon PJ, Peisach AR, Martin J. 2007. New models for old questions: Generalized 

linear models for cost prediction. Journal of Evaluation in Clinical practice 13(3):381–

389. 

Wu EQ, Birnbaum HG, Zhang HF, Ivanova JI, Yang E, Mallet D. 2007, Health care costs of 

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10 

Table 1. Number of trips and vessels observed 2005-2012. 

Table 2. Frequency of unique number of vessels observed. 

Table 3. Frequency and percentage of trips observed by length categories and by year. 
11 

Table 4. Frequency and percentage of trips observed by principal gear groups and by year. 

Table 5. Frequency and percentage of trips observed by principal species groups and by year, 

continued. 
12 

Table 6. Frequency and percentage of trips observed by principal species groups and by year. 

Table 7. Summary statistics of individual cost items over the analysis period (2008-2012). 

Table 8. Summary statistics of total costs at different levels of aggregations. 

Table 9. Summary Statistics of total cost by trip duration types and by length categories. 
13 

Table 10. Summary statistics of total cost of different trip types by gear categories. 

Table 11. Summary statistics of the continuous variables considered in model estimation. 
14 

Table 12. Frequency distribution of the discrete variables considered in model estimation. 

Table 13. Generalized Linear Model (GLM) parameter estimates using all observed trips. 
15 

Table 14. Summary statistics of the continuous variables considered in the prediction data. 

Table 15. Frequency distribution of the discrete variables in prediction data. 
16 

Table 16. Total trips costs observed and predicted. 

Table 17. Observed and predicted cost summaries by trip duration types and vessel length 

categories. 

Table 18. Summary statistics of observed and predicted costs by principal gear types. 
17 

Figure 1. Total cost distributions by trip duration types and vessel length categories. 
18 

Figure 2. Total cost distributions by vessels’ principal gear groups. 
19 

Figure 3. Histogram of the total cost distribution. 

 
20 

Figure 4. Distributions of predicted costs by trip duration types and vessel length categories. 
Publishing in NOAA Technical Memorandum NMFS-NE

Manuscript Qualification

This series represents a secondary level of scientific

publishing in the National Marine Fisheries Service (NMFS).

For all issues, the series employs thorough internal scientific

review, but not necessarily external scientific review. For most

issues, the series employs rigorous technical and copy editing.

Manuscripts that may warrant a primary level of scientific

publishing should be initially submitted to one of NMFS's

primary series (i.e., Fishery Bulletin, NOAA Professional Paper

NMFS, or Marine Fisheries Review).

Identical, or fundamentally identical, manuscripts should

not be concurrently submitted to this and any other publication

series. Manuscripts which have been rejected by any primary

series strictly because of geographic or temporal limitations

may be submitted to this series.

Manuscripts by Northeast Fisheries Science Center

(NEFSC) authors will be published in this series upon approval

by the NEFSC's Deputy Science & Research Director. Manuscripts by non-NEFSC authors may be published in this series

if: 1) the manuscript serves the NEFSC's mission; 2) the

manuscript meets the Deputy Science & Research Director's

approval; and 3) the author arranges for the printing and binding

funds to be transferred to the NEFSC's Research Communications Branch account from another federal account. For all

manuscripts submitted by non-NEFSC authors and published

in this series, the NEFSC will disavow all responsibility for the

manuscripts' contents; authors must accept such responsibility.

The ethics of scientific research and scientific publishing

are a serious matter. All manuscripts submitted to this series

are expected to adhere -- at a minimum -- to the ethical guidelines

contained in Chapter 2 ("Publication Policies and Practices") of

the Scientific Style and Format: the CSE Manual for Authors,

Editors, and Publishers, seventh edition (Reston VA: Council

of Science Editors). Copies of the manual are available at

virtually all scientific libraries.

edition of the United States Government Printing Office Style

Manual. That style manual is silent on many aspects of scientific

manuscripts. NEFSC publication and report series rely more on the

CSE Style Manual, seventh edition.

For in-text citations, use the name-date system. A special

effort should be made to ensure that the list of cited works contains

all necessary bibliographic information. For abbreviating serial

titles in such lists, use the guidance of the International Standards

Organization; such guidance is easily accessed through the various

Cambridge Scientific Abstracts’ serials source lists (see http://

www.public.iastate.edu/~CYBERSTACKS/JAS.htm). Personal communications must include date of contact and full name and mailing

address of source.

For spelling of scientific and common names of fishes, mollusks, and decapod crustaceans from the United States and Canada,

use Special Publications No. 29 (fishes), 26 (mollusks), and 17

(decapod crustaceans) of the American Fisheries Society (Bethesda

MD). For spelling of scientific and common names of marine

mammals, use Special Publication No. 4 of the Society for Marine

Mammalogy (Lawrence KS). For spelling in general, use the most

recent edition of Webster’s Third New International Dictionary of

the English Language Unabridged (Springfield MA: G. & C.

Merriam).

Typing text, tables, and figure captions: Text, tables, and

figure captions should be converted to Word. In general, keep text

simple (e.g., do not switch fonts and type sizes, do not use hard

returns within paragraphs, do not indent except to begin paragraphs). Also, do not use an automatic footnoting function; all notes

should be indicated in the text by simple numerical superscripts, and

listed together in an "Endnotes" section prior to the "References

Cited" section. Especially, do not use a graphics function for

embedding tables and figures in text.

Tables should be prepared with a table formatting function.

Each figure should be supplied in digital format (preferably GIF or

JPG), unless there is no digital file of a given figure. Except under

extraordinary circumstances, color will not be used in illustrations.

Manuscript Preparation

Organization: Manuscripts must have an abstract, table

of contents, and -- if applicable -- lists of tables, figures, and

acronyms. As much as possible, use traditional scientific

manuscript organization for sections: "Introduction," "Study

Area," "Methods & Materials," "Results," "Discussion" and/

or "Conclusions," "Acknowledgments," and "References Cited."

Style: All NEFSC publication and report series are

obligated to conform to the style contained in the most recent

Northeast Fisheries Science Center

Operations, Management & Information Division

Research Communications Branch

Editorial Office

Manuscript Submission

Authors must submit separate digital files of the manuscript

text, tables, and figures. The manuscript must have cleared

NEFSC's online internal review system. Non-NEFSC authors who

are not federal employees will be required to sign a "Release of

Copyright" form.

Send all materials and address all correspondence to: Jarita A.

Davis (Editor), Editorial Office, NMFS Northeast Fisheries Science Center, 166 Water Street, Woods Hole, MA 02543-1026.
National Marine Fisheries Service, NOAA

166 Water St.

Woods Hole, MA 02543-1026

Publications and Reports

of the

Northeast Fisheries Science Center

The mission of NOAA's National Marine Fisheries Service (NMFS) is "stewardship of living marine resources 

for the benefit of the nation through their science-based conservation and management and promotion of the 

health of their environment." As the research arm of the NMFS's Northeast Region, the Northeast Fisheries 

Science Center (NEFSC) supports the NMFS mission by "conducting ecosystem-based research and assessments of living marine resources, with a focus on the Northeast Shelf, to promote the recovery and long-term 

sustainability of these resources and to generate social and economic opportunities and benefits from their use." 

Results of NEFSC research are largely reported in primary scientific media (e.g., anonymously-peer-reviewed 

scientific journals). However, to assist itself in providing data, information, and advice to its constituents, the 

NEFSC occasionally releases its results in its own media. Currently, there are three such media:

NOAA Technical Memorandum NMFS-NE -- This series is issued irregularly. The series typically includes: data reports of 

long-term field or lab studies of important species or habitats; synthesis reports for important species or habitats; annual reports 

of overall assessment or monitoring programs; manuals describing program-wide surveying or experimental techniques; literature 

surveys of important species or habitat topics; proceedings and collected papers of scientific meetings; and indexed and/or annotated 

bibliographies. All issues receive internal scientific review and most issues receive technical and copy editing.

Northeast Fisheries Science Center Reference Document -- This series is issued irregularly. The series typically includes: data 

reports on field and lab studies; progress reports on experiments, monitoring, and assessments; background papers for, collected

abstracts of, and/or summary reports of scientific meetings; and simple bibliographies. Issues receive internal scientific review, but 

no technical or copy editing.

Resource Survey Report (formerly Fishermen's Report) -- This information report is a quick-turnaround report on the distribution 

and relative abundance of selected living marine resources as derived from each of the NEFSC's periodic research vessel surveys

of the Northeast's continental shelf. There is no scientific review, nor any technical or copy editing, of this report.

OBTAINING A COPY: To obtain a copy of a NOAA Technical Memorandum NMFS-NE or a Northeast Fisheries Science Center 

Reference Document, or to subscribe to the Resource Survey Report, either contact the NEFSC Editorial Office (166 Water St., 

Woods Hole, MA 02543-1026; 508-495-2228) or consult the NEFSC webpage on "Reports and Publications" (http://www.nefsc.

noaa.gov/nefsc/publications/).

ANY USE OF TRADE OR BRAND NAMES IN ANY NEFSC PUBLICATION OR REPORT DOES NOT IMPLY ENDORSEMENT.

MEDIA

 MAIL