In paul4forest/GFPMoutput: This program reads output simulation of the Global Forest Product Model (GFPM).

library(knitr)
library(dplyr)
library(ggplot2)
# Set same path for knitr evaluation as for interactive use
opts_knit$set(root.dir = '../..')
opts_chunk$set(fig.width=10)

Load functions and scenario data

load("enddata/GFPM_training_scenarios_with_historical.RDATA")
# Extract prices
gfpmprices <- gfpm %>% 
    filter(Element==  "DPrice" & !is.na(Country) ) %>%
    mutate(Volume = Volume /1000)
# Extract volume
gfpmvolume <- gfpm %>% filter(Element!=  "DPrice")


eu27countries <- GFPMoutput::countrycodes$Country[GFPMoutput::countrycodes$EU27]

Base scenario + other 2 training scenarios, calculated by changing the demand elasticities by plus or minus 1 standard error, corresponding to a confidence intereval of 70%.

Introduction

Explore country specific data. Unfortunately GFPM doesn't simulate bilateral trade.

Prices

for (product in unique(gfpmprices$Product)){
    pv <- ggplot(data=filter(gfpmvolume, Product == product & 
                           Country %in% eu27countries)) +
        aes(x=Year, y=Volume, color=Element, linetype=Scenario) +
        geom_line() + ylim(0,NA) + ylab("Volume") + xlim(1990, NA) +
        facet_wrap(~Country) + ggtitle(product)
    plot(pv)    
    pp <- ggplot(data=filter(gfpmprices, Product == product & 
                           Country %in% eu27countries)) +
        aes(x=Year, y=Volume, color=Element, linetype=Scenario) +
        geom_line() + ylim(0,NA) + ylab("$/T") + xlim(1990, NA) +
        facet_wrap(~Country) + ggtitle(paste(product, "Prices"))
    plot(pp)
}

ggplot(data=filter(gfpmprices, Product ==  "OthPaper")) +
    aes(x=Year, y=Volume, color=Element, linetype=Scenario) +
    geom_line() + ylim(0,NA) + ylab("$/T") + xlim(1990, NA) +
    facet_wrap(~Country, scales="free_y") + ggtitle("Prices")

paul4forest/GFPMoutput documentation built on May 24, 2019, 8:25 p.m.