Update to 2017 GDP Base Year

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '28699896'
+ValidationKey: '28784160'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'

CITATION.cff

@@ -2,8 +2,8 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'mrcommons: MadRat commons Input Data Library'
-version: 1.43.6
-date-released: '2024-09-20'
+version: 1.44.0
+date-released: '2024-09-23'
 abstract: Provides useful functions and a common structure to all the input data required
   to run models like MAgPIE and REMIND of model input data.
 authors:

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: mrcommons
 Type: Package
 Title: MadRat commons Input Data Library
-Version: 1.43.6
-Date: 2024-09-20
+Version: 1.44.0
+Date: 2024-09-23
 Authors@R: c(person("Benjamin Leon", "Bodirsky", email = "bodirsky@pik-potsdam.de", role = "aut"),
              person("Kristine", "Karstens", role = "aut"),
              person("Lavinia", "Baumstark", role = "aut"),

R/calcGTAPTotalTransportCosts.R

@@ -47,11 +47,11 @@ calcGTAPTotalTransportCosts <- function(costType = "transport", version = "9") {
   totalTcosts <- (tcostInputs + tcostToSecondary) / 2
 
   totalTcosts <-  GDPuc::convertGDP(totalTcosts, unit_in = "current US$MER",
-                                    unit_out = "constant 2005 US$MER",
+                                    unit_out = "constant 2017 US$MER",
                                     replace_NAs = "no_conversion")
 
   return(list(x = totalTcosts,
               weight = NULL,
-              unit = "million constant 2005 US$MER/yr",
+              unit = "million constant 2017 US$MER/yr",
               description = "Costs for GTAP commodities (half of input to market and market to value"))
 }

R/calcIniFoodPrice.R

@@ -9,7 +9,7 @@
 #' @param year Specifies the year for the initialization of prices in MAgPIE. Default is `y2005`.
 #' @param products subselection of products to be returned
 #'
-#' @return List with a magpie object with commodity prices on global level in $05/tDM.
+#' @return List with a magpie object with commodity prices on global level in $17/tDM.
 #' @author Mishko Stevanovic, Benjamin Leon Bodirsky
 #' @seealso
 #' [readIMPACT3.2.2World_Price()]
@@ -27,7 +27,7 @@ calcIniFoodPrice <- function(datasource = "FAO", year = "y2005", products = "kfo
   dm <- collapseNames(dm)
 
   if (datasource == "IMPACT3.2.2World_Price") {
-    out <- readSource("IMPACT3.2.2World_Price")
+    out <- readSource("IMPACT3.2.2World_Price") # in 2017 prices now
     # select scenario and initial year
     out <- collapseNames(out[, year, "SSP2-NoCC-NoCC-379"])
     out <- setYears(out, NULL)
@@ -69,6 +69,17 @@ calcIniFoodPrice <- function(datasource = "FAO", year = "y2005", products = "kfo
     out[, , "pasture"]          <- 50 # quick google search
     out[, , "scp"]              <- 1500 # using upper end prices similar to fishmeal
 
+    # [DC] At some point probably better to do another 'quick google search',
+    # for now convert these to 2017 values using US inflation, also for consistency
+    conv <- c("sugr_cane", "sugr_beet", "alcohol", "fish", "oilpalm", "oilcakes", "cottn_pro", "foddr",
+              "brans", "distillers_grain", "ethanol", "fibres", "molasses", "wood", "woodfuel", "begr",
+              "betr", "res_cereals", "res_fibrous", "pasture", "scp")
+    getItems(out, dim = 1) <- "USA"
+    out[, , conv] <- GDPuc::convertGDP(out[, , conv], unit_in = "constant 2005 US$MER",
+                                       unit_out = "constant 2017 US$MER",
+                                       replace_NAs = "no_conversion")
+    getItems(out, dim = 1) <- "GLO"
+
     # correct the prices for dry matter values
     out <- out[, , ] / dm[, , ]
 
@@ -106,6 +117,16 @@ calcIniFoodPrice <- function(datasource = "FAO", year = "y2005", products = "kfo
     out[, , "foddr"]            <- 50 # quick google search
     out[, , "sugar"]            <- 250 # quick google search
 
+    conv <- c("fish", "oilcakes", "brans", "distillers_grain", "ethanol", "alcohol",
+              "molasses", "wood", "woodfuel", "begr",
+              "betr", "res_cereals", "res_fibrous", "pasture", "scp",
+              "foddr", "sugar")
+    getItems(out, dim = 1) <- "USA"
+    out[, , conv] <- GDPuc::convertGDP(out[, , conv], unit_in = "constant 2005 US$MER",
+                                       unit_out = "constant 2017 US$MER",
+                                       replace_NAs = "no_conversion")
+    getItems(out, dim = 1) <- "GLO"
+
     # correct the prices from online sources for dry matter values
     out[, , missingCommodities] <- out[, , missingCommodities] / dm[, , missingCommodities]
 
@@ -120,7 +141,7 @@ calcIniFoodPrice <- function(datasource = "FAO", year = "y2005", products = "kfo
 
   return(list(x = out,
               weight = NULL,
-              unit = "US$05/tDM",
+              unit = "US$2017/tDM",
               description = description,
               isocountries = FALSE))
 }

R/calcMAgPIEReport.R

@@ -4,40 +4,15 @@ calcMAgPIEReport <- function(subtype) {
   x <- readSource("MAgPIE", subtype = "MAgPIEReport_extensive")
 
   if (subtype == "CostTotal") {
-    # with transformation factor from 10E6 US$2005 to 10E12 US$2005
-    x <- x[, , "Costs Without Incentives (million US$05/yr)"] / 1000 / 1000
-
-    # convert from US$2005 -> US$2017
-    x <- GDPuc::convertGDP(
-      gdp = x,
-      unit_in = "constant 2005 US$MER",
-      unit_out = mrdrivers::toolGetUnitDollar(),
-      replace_NAs = "with_USA"
-    )
-
-    getNames(x) <- gsub("US\\$05", "US\\$17", getNames(x))
-
+    # with transformation factor from 10E6 US$2017 to 10E12 US$2017
+    x <- x[, , "Costs Without Incentives (million US$17/yr)"] / 1000 / 1000
     d <- "Total Landuse Costs from MAgPIE excluding emission costs"
-    u <- "trillion US$2017/yr"
-
+    u <- "T$2017/yr"
   } else if (subtype == "CostMAC") {
-
-    # with transformation factor from 10E6 US$2005 to 10E12 US$2005
-    x <- x[, , "Costs Accounting|+|MACCS (million US$05/yr)"] / 1000 / 1000
-
-    # convert from US$2005 -> US$2017
-    x <- GDPuc::convertGDP(
-      gdp = x,
-      unit_in = "constant 2005 US$MER",
-      unit_out = mrdrivers::toolGetUnitDollar(),
-      replace_NAs = "with_USA"
-    )
-
-    getNames(x) <- gsub("US\\$05", "US\\$17", getNames(x))
-
+    # with transformation factor from 10E6 US$2017 to 10E12 US$2017
+    x <- x[, , "Costs Accounting|+|MACCS (million US$17/yr)"] / 1000 / 1000
     d <- "MAC Costs for LU emissions from MAgPIE"
-    u <- "trillion US$2017/yr"
-
+    u <- "T$2017/yr"
   } else if (subtype == "ProductionBiomass") {
     x <- x[, , "Demand|Bioenergy|2nd generation|++|Bioenergy crops (EJ/yr)"] / 31.536 # EJ to TWa
     d <- "Production of ligno-cellulosic purpose grown biomass in MAgPIE"
@@ -90,11 +65,11 @@ calcMAgPIEReport <- function(subtype) {
   getNames(x) <- getNames(x) %>%
     stringr::str_replace_all(c(
       "^C_"               = "",
-      #"-PkBudg900-mag-4"  = ".rcp20", # in 2022-10 still in emulator files
-      #"-PkBudg500-mag-4"  = ".rcp20", # in 2023-10 still in emulator files
+      # "-PkBudg900-mag-4"  = ".rcp20", # in 2022-10 still in emulator files
+      # "-PkBudg500-mag-4"  = ".rcp20", # in 2023-10 still in emulator files
       "-PkBudg650-mag-4"  = ".rcp20",
-      #"-PkBudg1300-mag-4" = ".rcp26", # in 2022-10 still in emulator files
-      #"-PkBudg1150-mag-4" = ".rcp26", # in 2023-10 still in emulator files
+      # "-PkBudg1300-mag-4" = ".rcp26", # in 2022-10 still in emulator files
+      # "-PkBudg1150-mag-4" = ".rcp26", # in 2023-10 still in emulator files
       "-PkBudg1050-mag-4" = ".rcp26",
       "-NDC-mag-4"        = ".rcp45",
       "-Base-mag-4"       = ".none",
@@ -103,7 +78,7 @@ calcMAgPIEReport <- function(subtype) {
     ))
 
   # add values for SSP3 copying the values from SSP2
-  tmp <- x[,,"SSP2"]
+  tmp <- x[, , "SSP2"]
   getNames(tmp) <- gsub("SSP2", "SSP3", getNames(tmp))
   x <- mbind(x, tmp)
 

R/calcPriceAgriculture.R

@@ -37,7 +37,7 @@
 #' @importFrom reshape2 melt acast
 #'
 
-calcPriceAgriculture <- function(datasource = "IMPACT3.2.2World_Price", unit = "US$05/tDM") {
+calcPriceAgriculture <- function(datasource = "IMPACT3.2.2World_Price", unit = "US$17/tDM") {
 
   if (datasource == "IMPACT3.2.2World_Price") {
 
@@ -70,7 +70,7 @@ calcPriceAgriculture <- function(datasource = "IMPACT3.2.2World_Price", unit = "
 
   } else if (datasource == "WBGEM") {
 
-    # Prices in US$05/tDM
+    # Prices in US$17/tDM
     x <- calcOutput("WBGEM", aggregate = FALSE)
 
     # sectoral mappings
@@ -138,7 +138,7 @@ calcPriceAgriculture <- function(datasource = "IMPACT3.2.2World_Price", unit = "
 
   } else if (datasource == "FAO") {
 
-    # Annual producer prices in US$05/tDM
+    # Annual producer prices in US$17/tDM
     out         <- readSource("FAO_online", subtype = "PricesProducerAnnual", convert = TRUE)
     aggregation <- toolGetMapping("FAOitems_online.csv",
                                   type = "sectoral", where = "mappingfolder")
@@ -184,10 +184,10 @@ calcPriceAgriculture <- function(datasource = "IMPACT3.2.2World_Price", unit = "
     isocountries <- TRUE
   }
 
-  if (unit != "US$05/tDM") {
+  if (unit != "US$17/tDM") {
     # Transform to selected currency unit
     out <- GDPuc::convertGDP(out,
-                             unit_in = "constant 2005 US$MER",
+                             unit_in = "constant 2017 US$MER",
                              unit_out =  unit,
                              replace_NAs = "no_conversion")
   }

R/calcWBGEM.R

@@ -21,7 +21,7 @@ calcWBGEM <- function() {
                                  setNames(x[, , grep("nominal", sugar, value = TRUE)], NULL), NULL)
   adjustFactor2005 <- 1 / setYears(x[, 2005, grep("real", sugar, value = TRUE)] /
                                      setNames(x[, 2005, grep("nominal", sugar, value = TRUE)], NULL), NULL) *
-                                       adjustFactor2010
+    adjustFactor2010
   adjustFactor2005 <- setNames(adjustFactor2005, NULL)
 
   vars <- grep("nominal", getNames(x), value = TRUE)
@@ -45,8 +45,15 @@ calcWBGEM <- function() {
   out <- out * adjustFactor2005
   out[is.na(out)] <- 0
 
+  # inflate to 2017 using US inflation for global value
+  getItems(out, dim = 1) <- "USA"
+  out <- GDPuc::convertGDP(out, unit_in = "constant 2005 US$MER",
+                           unit_out = "constant 2017 US$MER",
+                           replace_NAs = "no_conversion")
+  getItems(out, dim = 1) <- "GLO"
+
   return(list(x = out,
-              unit = "real2005 USD per ton",
+              unit = "real2017 USD per ton",
               weight = NULL,
               description = "WBGEM global price of commodity"))
 }

R/convertGTAPv8v9.R

@@ -66,10 +66,8 @@ convertGTAPv8v9 <- function(x, subtype) {
 
   } else {
     gdpMer <- calcOutput("GDPPast", GDPPast = "WDI-MI",
-                         unit = "constant 2005 US$MER", aggregate = FALSE)
+                         unit = "constant 2017 US$MER", aggregate = FALSE)
     gdpMer <- gdpMer[, getYears(x), , drop = TRUE]
-
-
     w1 <- GDPuc::convertGDP(gdpMer,
                             unit_in = "constant 2017 US$MER",
                             unit_out = "current US$MER",

R/convertICP2017.R

@@ -1,7 +1,7 @@
 #' @title convertICP2017
 #' @description  converts data of World Bank ICP round, downloaded from
 #' here: https://databank.worldbank.org/source/icp-2017
-#' mainly a currency conversion to MER05. Assume that in the original dataset,
+#' mainly a currency conversion to MER2017. Assume that in the original dataset,
 #' 2011 values are in 2011MER and 2017 in 2017MER, given the ICP rounds
 #'
 #' @param subtype data subtype needed. Either "priceLevel", or "per_cap_exp"
@@ -17,29 +17,33 @@ convertICP2017 <- function(x, subtype = "per_cap_expMER") {
   # currency convert for expenditures
   if (subtype == "per_cap_expMER") {
 
-    x2011 <- GDPuc::convertGDP(x[, 2011, ], unit_in = "constant 2011 US$MER", unit_out = "constant 2005 US$MER")
-    x2017 <- GDPuc::convertGDP(x[, 2017, ], unit_in = "constant 2017 US$MER", unit_out = "constant 2005 US$MER")
+    x2011 <- GDPuc::convertGDP(x[, 2011, ],
+                               unit_in = "constant 2011 US$MER",
+                               unit_out = "constant 2017 US$MER")
+    x2017 <- x[, 2017, ]
     x <- mbind(x2011, x2017)
     x[is.na(x)] <- 0
   }
 
   # currency convert for expenditures
   if (subtype == "per_cap_expPPP") {
 
-    x2011 <- GDPuc::convertGDP(x[, 2011, ], unit_in = "constant 2011 US$PPP", unit_out = "constant 2005 US$MER")
-    x2017 <- GDPuc::convertGDP(x[, 2017, ], unit_in = "constant 2017 US$PPP", unit_out = "constant 2005 US$MER")
+    x2011 <- GDPuc::convertGDP(x[, 2011, ],
+                               unit_in = "constant 2011 US$PPP",
+                               unit_out = "constant 2017 US$MER")
+    x2017 <- x[, 2017, ]
     x <- mbind(x2011, x2017)
     x[is.na(x)] <- 0
   }
 
   # remove aggregate categories
 
   x <- x[, , c("GROSS DOMESTIC PRODUCT",
-             "FOOD AND NON-ALCOHOLIC BEVERAGES",
-             "ALCOHOLIC BEVERAGES, TOBACCO AND NARCOTICS",
-             "HOUSEHOLDS AND NPISHS FINAL CONSUMPTION EXPENDITURE",
-             "INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS WITHOUT HOUSING",
-             "GENERAL GOVERNMENT FINAL CONSUMPTION EXPENDITURE"), invert = TRUE]
+               "FOOD AND NON-ALCOHOLIC BEVERAGES",
+               "ALCOHOLIC BEVERAGES, TOBACCO AND NARCOTICS",
+               "HOUSEHOLDS AND NPISHS FINAL CONSUMPTION EXPENDITURE",
+               "INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS WITHOUT HOUSING",
+               "GENERAL GOVERNMENT FINAL CONSUMPTION EXPENDITURE"), invert = TRUE]
 
 
   return(x)