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02_PrepPrices.R
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02_PrepPrices.R
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#---------------------------------------------------#
# #
# This program organizes the German-level input and #
# output price indexes from Destatis / Genesis #
# #
#---------------------------------------------------#
# Open packages
library(dplyr)
library(readxl)
library(cellranger)
library(reshape2)
# load data, melt, rename
wi_raw <- read_excel("Data/destatis_inputs_61221-0002.xlsx", sheet = "61221-0002", range = "A6:BU40", col_names = TRUE)
wi_raw[wi_raw=="-"]<-NA
wi <- melt(wi_raw, id.vars="...1")
wi <- dplyr::rename(wi, c("input"="...1", "year"="variable", "wi"="value"))
#reshape
wi_nuts0 <- reshape(wi, idvar = "year", timevar = "input", direction = "wide")
#rename columns
colnames(wi_nuts0)
wi_nuts0 <- dplyr::rename(wi_nuts0,
c("wi_inputs"="wi.Landwirtschaftliche Betriebsmittel insgesamt",
"wi_mat_serv"="wi.Waren und Dienstleist. des lfd. landw. Verbrauchs",
"wi_seed"="wi.Saat- und Pflanzgut",
"wi_energy"="wi.Energie und Schmierstoffe",
"wi_heating"="wi.Heizstoffe",
"wi_fuel"="wi.Treibstoffe",
"wi_electricity"="wi.Elektrischer Strom",
"wi_lubricants"="wi.Schmierstoffe",
"wi_fert"="wi.Düngemittel",
"wi_pest"="wi.Pflanzenschutzmittel",
"wi_fung"="wi.Fungizide",
"wi_insect"="wi.Insektizide",
"wi_herb"="wi.Herbizide",
"wi_feed"="wi.Futtermittel",
"wi_singlefeed"="wi.Einzelfuttermittel",
"wi_wheatprod"="wi.Getreide und Mühlennachprodukte",
"wi_oilkake"="wi.Ölkuchen und -schrot",
"wi_compoundfeed"="wi.Mischfuttermittel",
"wi_compf_cattle"="wi.Mischfuttermittel für Rinder",
"wi_compf_hogs"="wi.Mischfuttermittel für Schweine",
"wi_compf_poultry"="wi.Mischfuttermittel für Geflügel",
"wi_vet"="wi.Veterinärleistungen",
"wi_maint_mach_mat"="wi.Instandhaltung von Maschinen und Material",
"wi_maint_build"="wi.Instandhaltung von Bauten",
"wi_othermatserv"="wi.Sonstige Waren und Dienstleistungen",
"wi_invest"="wi.Waren und Dienstleist. landwirt. Investitionen",
"wi_material"="wi.Material",
"wi_machinery"="wi.Maschinen und sonstige Ausrüstungsgüter",
"wi_cropsmachinery"="wi.Maschinen und Geräte für Kulturen",
"wi_harvesters"="wi.Maschinen und Geräte für die Erntebergung",
"wi_vehicles"="wi.Fahrzeuge",
"wi_tractors"="wi.Zugmaschinen",
"wi_othervehicles"="wi.Sonstige Fahrzeuge",
"wi_buildings"="wi.Bauten"))
#-------------------------------------------#
# Translate marketing years to actual years #
#-------------------------------------------#
# Note: The variable "year" in the farm data refers to the second part of the marketing year
# (i.e., 2018 means marketing year 2017/18)
#take digits 1 and 2 as well as digits 6 and 7 from the original variable
wi_nuts0$year <- paste0(substr(wi_nuts0$year, 1, 2),
substr(wi_nuts0$year, 6, 7))
#Correct the 1900 (from 1999/00)
wi_nuts0$year[wi_nuts0$year==1900] <- 2000
# Make data numeric
wi_nuts0 <- as.data.frame(lapply(wi_nuts0,as.numeric))
# save price data
save(wi_nuts0,file="rOutput/wi_nuts0.Rda")