In emilyhmarkowitz/FisheriesEconomicProductivityIndex: What the Package Does (One Line, Title Case)

knitr::opts_chunk$set(echo = FALSE, error = FALSE, message = FALSE, warning = FALSE)

Measuring Output for U.S. Commercial Fisheries From Theory to Practice

Emily Markowitz^1^ (Emily.Markowitz AT noaa.gov)

Sun Ling Wang^2^ (Sun-Ling.Wang AT noaa.gov)

^1^Contractor, ECS Federal in support of NOAA Fisheries Office of Science and Technology Economics & Social Analysis Division; as of Sept. 28, 2020: Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA 98195

^2^On detail with the NOAA Fisheries Office of Science and Technology Economics & Social Analysis Division

*The views expressed are those of the author and should not be attributed to the NOAA, ECS or ERS

GitHub: https://github.com/emilyhmarkowitz/FishEconProdOutput

NOAA README

This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an ‘as is’ basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.

Download this package

library(devtools)
devtools::install_github("emilyhmarkowitz/FishEconProdOutput", dependencies = TRUE)
library(FishEconProdOutput)

echoTF<-function(typical, code = TRUE) {
  return(ifelse(code == TRUE, typical, FALSE))
}

code<-FALSE
showresults<-FALSE

dir.in<-getwd()
#Local Directories
dir.output<-paste0(dir.in, "/output/")
dir.data<-paste0(dir.in, "/data/")

#####LOAD CRAN LIBRARIES#######

#Seperating species by taxonomic group
# install.packages("remotes")
# remotes::install_github("ropensci/taxize")
library(taxize)

# Data Managment
library(tidyr)
library(reshape2)
library(tidyverse)
library(filesstrings)
library(data.table) # := to tag species codes
require(plyr)  #ddply function
library(sas7bdat)
library(rlist)

#RMarkdown
library(rmarkdown)
library(knitr)
library(gridExtra)
library(ggpubr)

#Excel File Management
library(officer)
library(xlsx)
library(readxl)

#Visuals
library(ggplot2)

#Package Management
library(roxygen2)
library(devtools)

#Presentations
#remotes::install_github('yihui/xaringan')
library(xaringan)
options(htmltools.dir.version = FALSE)
library(tidyverse)
library(stargazer)


options(java.parameters = "-Xmx1000m")
options(scipen=10000)

ln<-log #tricky, tricky, Base R! Didn't fool me this time!!!

Study Purpose

Develop alternative approaches to measure national and regional fishery outputs for productivity measurements.
Evaluate the impacts of missing data and other issues on output estimates.

Data requirements and source

The Tornqvist quantity index requires data on quantity and revenue shares. We employ landings quantity (pounds) and landings value ($USD) data by year, state, and species.

Data source: Fisheries One Stop Shop downloaded August 13 2020
More information about the data: Commericial Fisheries Landings Data

Documentation

For specifics about how the Quantitative and Price Methods are derived, please read this Documentation.

File Organization

Main fuctions of interest are:

PriceMethodOutput
PriceMethodOutput.Category
QuantityMethodOutput
QuantityMethodOutput.Category

Theoretical Framework: Törnqvist index

A Flexible Function and Superlative Quantity Index (Diewert 1976)

Math Theory: General Total Factor Productivity ($TFP$) Equation

The general form of the $TFP$ can be measured as aggregate output ($Y$) divided by real total inputs ($X$). Rates of TFP growth are constructed using the Törnqvist index approach. The TFP growth over two time periods is defined as:

$$ln(TFP_t/TFP_{t-1}) = \sum_{i=1}^n((\frac{R_{t,i} + R_{t-1,i}}{2}) * ln(\frac{Y_{t,i}}{Y_{t-1,i}}))) - \sum_{j=1}^m((\frac{W_{j,t} + W_{j,t-1}}{2}) * ln(\frac{X_{j,t}}{X_{j,t-1}})))$$

Such that:

Output represents $\sum_{i=1}^n((\frac{R_{it} + R_{it-1}}{2}) * ln(\frac{Y_{it}}{Y_{it-1}}))$
Input represents $\sum_{j=1}^n((\frac{W_{jt} + W_{jt-1}}{2}) * ln(\frac{X_{jt}}{X_{jt-1}}))$

where:

$Y_i$ = individual outputs. This will later be refered to as $Q_i$ in the following equations.
$X_j$ = individual inputs
$R_i$ = output revenue shares
$W_j$ = input cost shares
$t$ and $t-1$ = time, where 1 is the minimum year in the dataset
$i$ = fishery category, e.g., Finfish (=1), Shellfish (=2)
$s$ = species, e.g., Salmon, Alewife, Surf Clams