68 Comdat Profitability Indices
Description:
Found in: State of the Ecosystem - Mid-Atlantic (2026), State of the Ecosystem - New England (2026), State of the Ecosystem - Indicator Catalog (2026+)
Indicator category:
Contributor(s): Samantha Werner
Data steward: Samantha Werner samantha.werner@noaa.gov
Point of contact: Samantha Werner samantha.werner@noaa.gov
Public availability statement:
68.1 Methods
68.1.1 Data sources
Trip Costs – Trip Cost Model Estimates (POC Samantha Werner) Revenue – ecodata (commercial_bennet.rds) GDP Price Deflator– Bureau of Economic Analysis (BEA) Latitudes and Longitudes – CAMS_GARFO.CAMS_SUBTRIP EPU data – Ecodata (epu_sf)
68.1.2 Data analysis
The cost index tracks the relative change in real trip costs over time by calculating the geometric mean.The index is calculated by first normalizing individual trip costs against a constant reference value to create a trip-level ratio, where the constant reference value is the average of all trips from the study area in calendar year 2000 (i.e., the minimum year in the time series). The function then aggregates these ratios by year using a geometric mean, calculated via the log-transform method. Lastly, the time series
values are re-based to a specific target year by dividing each annual geometric mean by the mean of that base year, resulting in a standardized index where the base year equals 1.000. The revenue index tracks the performance of total commercial fishing revenue over time, relative to the average revenue from GB, GOM and MAB from the minimum year in the dataset. In this case, this is the calendar year 2000. This is accomplished by first scaling annual total revenues against the 2000 average annual revenue of the three area sums. Values are then rebased by dividing each year's index value by the base year index value such that calendar year 2000 is equal to 1.000. Note, this index does not use the geometric mean as it is obtaining the aggregate fleet performance rather than the average trip-level information. Lastly, a Profitability Index is derived by calculating the ratio of the Revenue Index to the Cost Index, where values greater than 1.000 indicate that revenue growth has outpaced cost increases relative to the base year which, in this case, is calendar year 2000.
68.1.3 Data processing
Trip cost data, developed from the trip cost model run by Samantha Werner are derived from the static files on the NEFSC network drive. The cost information is a composite variable of trip cost information consisting of fuel, bait, groceries, water, ice, oil and general supplies. Note, that this cost variable does not include labor costs (crew or hired captain payments). There are decision rules within the models (one model pertaining to data from 2000-2009 and another for 2010-2024) which can be found within their respective folders on the network drive. The trip cost models have been adapted from methods described in Werner et al. 2020 (Werner et al. 2020). Latitude and longitudinal information sourced from CAMS_GARFO.CAMS_SUBTRIP and merged with the trip cost information. The data are then allocated to EPUs using Ecodata (epu_sf) for GB, GOM and MAB. Revenue data are derived from EcoData (commercial_bennet.rds) for all U.S. landings where the species value is greater than zero. All values are deflated to 2024 constant dollars using the Bureau of Economic Analysis (BEA) Gross Domestic Product Implicit Price Deflator which is pulled directly from the BEA into R.
catalog link https://noaa-edab.github.io/catalog/comdat_profit.html