Update to 2017 GDP Base Year

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '12226536'
+ValidationKey: '12393180'
 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: 'mrland: MadRaT land data package'
-version: 0.61.2
-date-released: '2024-09-12'
+version: 0.62.0
+date-released: '2024-09-23'
 abstract: The package provides land related data via the madrat framework.
 authors:
 - family-names: Dietrich

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mrland
 Title: MadRaT land data package
-Version: 0.61.2
-Date: 2024-09-12
+Version: 0.62.0
+Date: 2024-09-23
 Authors@R: c(
     person("Jan Philipp", "Dietrich", , "dietrich@pik-potsdam.de", role = c("aut", "cre")),
     person("Abhijeet", "Mishra", role = "aut"),

R/calcAfforestCosts.R

@@ -30,5 +30,5 @@ calcAfforestCosts <- function() {
   l <- setYears(readSource("FAO_online","Land")[,2001,"6601|Land area.Area_(1000_ha)",drop=TRUE],NULL)
   l[is.na(l)|is.nan(l)] <- 0
 
-  return(list(x=x,weight=l,unit="US$2004/ha",description="Afforestation factor requirement costs"))
+  return(list(x=x,weight=l,unit="US$2017/ha",description="Afforestation factor requirement costs"))
 }

R/calcGDPdeflator.R

@@ -0,0 +1,39 @@
+#' @title calcGDPdeflator
+#' @description calculates a iso-level deflator,
+#' this is needed to run food demand and livestock regressions consistently
+#' @param yearFrom year in "y2005" format
+#' @param yearTo year in "y2005" format
+#' @param currency "PPP" or "MER"
+#' @return List of magpie objects with results on country level, weight on country level, unit and description.
+#' @author David Chen
+#' @importFrom GDPuc convertGDP
+
+calcGDPdeflator <- function(yearFrom = 2017, yearTo = 2005, currency = "PPP") {
+
+  reg <- getItems(calcOutput("GDP", unit = "constant 2005 Int$PPP",
+                             naming = "scenario",
+                             aggregate = FALSE), dim = 1)
+
+  defl2017 <- new.magpie(cells_and_regions = reg,
+                         years = NULL,
+                         names = NULL,
+                         fill = 1)
+
+  if (currency == "PPP") {
+    unit <- "Int$PPP"
+  } else if (currency == "MER") {
+    unit <- "US$MER"
+  }
+
+  defl2017 <- convertGDP(defl2017,
+                         unit_in = paste("constant", yearFrom, unit, sep = " "),
+                         unit_out = paste("constant", yearTo, unit, sep = " "),
+                         replace_NAs = c("linear", "no_conversion"))
+  getNames(defl2017) <- NULL
+
+  return(list(x = defl2017,
+              weight = NULL,
+              unit = "$/$",
+              description = "GDP base year deflator"))
+
+}

R/calcGHGPrices.R

@@ -68,7 +68,11 @@ calcGHGPrices <- function(emissions = "pollutants", datasource = "REMMAG", rev =
     x[, , setToZero] <- 0
 
     description <- "GHG certificate prices for different scenarios based on data from REMIND-MAgPIE coupling"
-
+
+    #convert these to 2017$ here
+    x <- convertGDP(x, unit_in = "constant 2005 US$MER",
+                       unit_out = "constant 2017 US$MER",
+                       replace_NAs = "no_conversion")
 
   } else if (datasource == "Strefler2021") {
     x <- readSource("Strefler2021", subtype = paste0("intensive_", rev))
@@ -99,6 +103,12 @@ calcGHGPrices <- function(emissions = "pollutants", datasource = "REMMAG", rev =
     # swap dimensions (scenario and gas) such that in the output file gas is in lines and scenarios in columns
     getNames(x) <- gsub("^([^\\.]*)\\.(.*$)", "\\2.\\1", getNames(x))
 
+    # convert these to 2017$ here
+    x <- convertGDP(x, unit_in = "constant 2005 US$MER",
+                       unit_out = "constant 2017 US$MER",
+                       replace_NAs = "no_conversion")
+
+
     description <- paste("GHG certificate prices for different scenarios taken",
                          "from Strefler et al 2021 (DOI 10.1038/s41467-021-22211-2)")
 
@@ -115,14 +125,18 @@ calcGHGPrices <- function(emissions = "pollutants", datasource = "REMMAG", rev =
     } else if (emissions != "ghg") {
       stop("unknown emission type")
     }
+
+    #convert these to 2017$ here
+    x <- convertGDP(x, unit_in = "constant 2005 US$MER",
+                       unit_out = "constant 2017 US$MER",
+                       replace_NAs = "no_conversion")
 
     description <- "ghg certificate prices for different scenarios based on data from REMIND-MAgPIE-coupling"
 
-
   } else if (datasource == "SSPResults") {
 
     x <- readSource("SSPResults")
-    x <- collapseNames(x[, , "Price|Carbon (US$2005/t CO2)"])
+    x <- collapseNames(x[, , "Price|Carbon (US$2017/t CO2)"])
     x <- x * 44 / 12
 
     pollutants <- findset("pollutants")
@@ -191,6 +205,11 @@ calcGHGPrices <- function(emissions = "pollutants", datasource = "REMMAG", rev =
     # fill missing years in the future
     x <- time_interpolate(x, seq(1995, 2150, 5), extrapolation_type = "constant")
 
+    #convert these to 2017$ here
+    x <- convertGDP(x, unit_in = "constant 2005 US$MER",
+                       unit_out = "constant 2017 US$MER",
+                       replace_NAs = "no_conversion")
+
     description <- "ghg certificate prices for different scenarios based on CO2 prices provided by IMAGE"
 
   } else if (datasource == "SSP_and_REM") {
@@ -218,7 +237,7 @@ calcGHGPrices <- function(emissions = "pollutants", datasource = "REMMAG", rev =
   pop <- calcOutput("Population", aggregate = FALSE)
 
   return(list(x = x, weight = pop[, 2010, 1],
-              unit = "US$ 2005 per t N2O-N CH4 and CO2-C",
+              unit = "US$ 2017 per t N2O-N CH4 and CO2-C",
               description = description,
               note = "As weight for aggregation currently population data from 2010 is used.",
               min = 0,

R/calcIrrigationInvCosts.R

@@ -1,54 +1,70 @@
 #' @title calcIrrigationInvCosts
-#' 
-#' @description This function calculates irrigation investment costs for each country until the year 2050. 
-#' Values linearly converge towards the value of Germany (1995) by 2050.
-#' 
+#'
+#' @description This function calculates irrigation investment costs for each country until
+#'              the year 2050. Values linearly converge towards the value of Germany (1995)
+#'              by 2050.
+#'
 #' @return MAgPIE object
-#' 
+#'
 #' @author Nele Steinmetz, Felicitas Beier
-#' 
+#'
 #' @seealso \code{\link{calcOutput}}, \code{\link{readWBirrigation}},
 #' \code{\link{convertWBirrigation}}
-#' 
+#'
 #' @examples
-#' \dontrun{ 
+#' \dontrun{
 #' calcOutput("IrrigationInvCosts")
 #' }
-#' 
-#' @import magclass 
-#' 
+#'
+#' @import magclass
+#'
 calcIrrigationInvCosts <- function() {
-
-  # Investment costs for expanding irrigation infrastructure in US$ per hectare
+
+  # Investment costs for expanding irrigation infrastructure in 1000 US$ per hectare
+  # Note: in World Bank report (William I. Jones, 1991), p. 98, given in US$ per hectare
+  # But: csv table has transformed values (in 1000 US$ per hectare)
   WBirrigation           <- readSource("WBirrigation")
   getYears(WBirrigation) <- NULL
-  
+
   # irrigation cost constant until 2015
-  data              <- new.magpie(getRegions(WBirrigation), 1995:2050, "ad_unit_cost")
-  data[,1995:2050,] <- WBirrigation
+  data              <- new.magpie(cells_and_regions = getRegions(WBirrigation),
+                                  years = 1995:2050,
+                                  names = "ad_unit_cost",
+                                  fill = NA)
+  data[, 1995:2050, ] <- WBirrigation
+
+  # Transform fromm 1000 USD$ per hectare to US$ per hectare
+  data <- data * 1000
+
   # conversion: $1995 to $2004
-  data              <- data * 1000 * 1.19
-
+  data <- convertGDP(data,
+                     unit_in = "constant 1995 US$MER",
+                     unit_out = "constant 2017 US$MER",
+                     replace_NAs = "no_conversion")
+
   # from 2015 onwards, data converges to value of Germany until 2050
-  data_DEU <- new.magpie(getRegions(WBirrigation), 1995:2050, "ad_unit_cost", fill=as.numeric(data["DEU","y1995",]))
-
-  years <- new.magpie("GLO", getYears(data), NULL, getYears(data,as.integer=TRUE))                                                 
-  pos        <- (years - 2015) / (2050 - 2015)
-  pos[pos<0] <- 0
-  pos[pos>1] <- 1
-
-  data <- data_DEU*pos + data*(1-pos)
-  
+  dataDEU <- new.magpie(cells_and_regions = getRegions(WBirrigation),
+                         years = 1995:2050,
+                         names = "ad_unit_cost",
+                         fill = as.numeric(data["DEU", "y1995", ]))
+
+  data <- convergence(origin = data, aim = dataDEU,
+                      start_year = "y2015", end_year = "y2050",
+                      type = "linear")
+
   # expand this value until 2150
-  time_extend    <- paste0("y", seq(2055,2150,5))
-  data           <- time_interpolate(data, time_extend, extrapolation_type="constant", integrate_interpolated_years=TRUE)
+  timeExtend <- paste0("y", seq(2055, 2150, 5))
+  data       <- time_interpolate(data, timeExtend,
+                                 extrapolation_type = "constant",
+                                 integrate_interpolated_years = TRUE)
   getNames(data) <- NULL
-
-  # aggregation weight and transform from 1000ha to ha
-  w <- readSource("FAO_online", subtype="Land", convert=T)[,1995,"6610|Agricultural land.Area_(1000_ha)"] * 1000
-
-  return(list(x=data,
-              weight=w,
-              unit="US$2004", 
-              description="unit cost for irrigation expansion"))
+
+  # aggregation weight and transform from 1000ha to Mha
+  w <- readSource("FAO_online", subtype = "Land",
+                  convert = TRUE)[, 1995, "6610|Agricultural land.Area_(1000_ha)"] * 1000
+
+  return(list(x = data,
+              weight = w,
+              unit = "US$MER2017",
+              description = "unit cost for irrigation expansion"))
 }

R/calcTradeMargin.R

@@ -143,19 +143,18 @@ calcTradeMargin <- function(gtap_version = "GTAP9", bilateral = FALSE, producer_
   weight[, , "distillers_grain"] <- weight[, , "tece"]
 
   if (gtap_version == "GTAP9") {
-    if (!bilateral) {
       out <- GDPuc::convertGDP(out, unit_in = "current US$MER",
-                               unit_out = "constant 2005 US$MER",
+                               unit_out = "constant 2017 US$MER",
                                replace_NAs = "no_conversion")
-    }
+
     out <- setYears(out[, 2011, ], NULL)
     weight <- setYears(weight[, 2011, ], NULL)
   } else {
     out <- setYears(out, NULL)
     weight <- setYears(weight, NULL)
   }
 
-  unit <- "US$05"
+  unit <- "US$2017"
   description <- "Trade margins"
 
   # add tiny value to weight to avoid 0 weights creating 0 values

R/calcTradeTariff.R

@@ -112,11 +112,10 @@ calcTradeTariff<- function(gtap_version = "GTAP9", type_tariff = "total", bilate
     p <- add_dimension(p, dim = 1.2,   nm = getItems(p, dim = 1))
   }
   if (gtap_version == "GTAP9") {
-    if (!bilateral) {
       y <- GDPuc::convertGDP(y, unit_in = "current US$MER",
-                             unit_out = "constant 2005 US$MER",
+                             unit_out = "constant 2017 US$MER",
                              replace_NAs = "no_conversion")
-    }
+
     y <- setYears(y[, 2011, ], NULL)
   }
 
@@ -164,7 +163,7 @@ calcTradeTariff<- function(gtap_version = "GTAP9", type_tariff = "total", bilate
 
 
   description <- paste0(type_tariff, "trade tariff")
-  unit <- "USD05MER/tDM"
+  unit <- "US$2017/tDM"
   return(list(x = out,
               weight = weight,
               unit = unit,

R/calcValueProduction.R

@@ -40,7 +40,7 @@ x <- prod[regions, , common] * prices[regions, , common]
 }
 return(list(x = x,
             weight = NULL,
-            unit = "US$05/tDM",
+            unit = "US$2017/tDM",
             description = "Crop Production Value",
             min = 0,
             max = Inf,

R/convertSathayeForest.R

@@ -13,10 +13,13 @@
 #' }
 #' 
 convertSathayeForest <- function(x) {
-
-  # convert data from $US-2000 into $US-2004
-  x <- x * 1.091
+
+  # convert data from $US-2000 into $US-2017
   y <- toolAggregate(x, "regionmappingSathayeForest.csv", weight=NULL )
-
+  y <- convertGDP(y, unit_in = "constant 2000 US$MER",
+                      unit_out = "constant 2017 US$MER",
+                      replace_NAs = "no_conversion")
+
+
   return(y)
 }

R/fullMAGPIE.R

@@ -44,13 +44,14 @@ fullMAGPIE <- function(rev = numeric_version("0.1"), dev = "") {
 
   # 09 drivers
   calcOutput("GDP",
+             unit = "constant 2017 Int$PPP",
              naming = "scenario",
              aggregate = FALSE,
              years = magYears,
              round = 3, # please dont increase rounding, this can create errors
              file = "f09_gdp_ppp_iso.csv")
   calcOutput("GDP",
-             unit = "constant 2005 US$MER",
+             unit = "constant 2017 US$MER",
              naming = "scenario",
              aggregate = FALSE,
              years = magYears,
@@ -76,6 +77,8 @@ fullMAGPIE <- function(rev = numeric_version("0.1"), dev = "") {
              round = 6) # please dont increase rounding, this can create errors
   calcOutput("PhysicalInactivity", aggregate = FALSE, years = magYears, round = 3,
              file = "f09_physical_inactivity.cs3")
+  calcOutput("GDPdeflator", aggregate = FALSE, round = 3, file = "fm_gdp_defl_ppp.cs4",
+             currency = "PPP")
 
   # 13 tc
   calcOutput("ExoTcDummy",       round = 4, file = "f13_tau_scenario.csv", aggregate = superregion)

README.md

@@ -1,6 +1,6 @@
 # MadRaT land data package
 
-R package **mrland**, version **0.61.2**
+R package **mrland**, version **0.62.0**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/mrland)](https://cran.r-project.org/package=mrland) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3822083.svg)](https://doi.org/10.5281/zenodo.3822083) [![R build status](https://github.com/pik-piam/mrland/workflows/check/badge.svg)](https://github.com/pik-piam/mrland/actions) [![codecov](https://codecov.io/gh/pik-piam/mrland/branch/master/graph/badge.svg)](https://app.codecov.io/gh/pik-piam/mrland) [![r-universe](https://pik-piam.r-universe.dev/badges/mrland)](https://pik-piam.r-universe.dev/builds)
 
@@ -39,7 +39,7 @@ In case of questions / problems please contact Jan Philipp Dietrich <dietrich@pi
 
 To cite package **mrland** in publications use:
 
-Dietrich J, Mishra A, Weindl I, Bodirsky B, Wang X, Baumstark L, Kreidenweis U, Klein D, Steinmetz N, Chen D, Humpenoeder F, von Jeetze P, Wirth S, Beier F, Hoetten D, Sauer P (2024). _mrland: MadRaT land data package_. doi:10.5281/zenodo.3822083 <https://doi.org/10.5281/zenodo.3822083>, R package version 0.61.2, <https://github.com/pik-piam/mrland>.
+Dietrich J, Mishra A, Weindl I, Bodirsky B, Wang X, Baumstark L, Kreidenweis U, Klein D, Steinmetz N, Chen D, Humpenoeder F, von Jeetze P, Wirth S, Beier F, Hoetten D, Sauer P (2024). _mrland: MadRaT land data package_. doi: 10.5281/zenodo.3822083 (URL: https://doi.org/10.5281/zenodo.3822083), R package version 0.62.0, <URL: https://github.com/pik-piam/mrland>.
 
 A BibTeX entry for LaTeX users is
 
@@ -48,8 +48,8 @@ A BibTeX entry for LaTeX users is
   title = {mrland: MadRaT land data package},
   author = {Jan Philipp Dietrich and Abhijeet Mishra and Isabelle Weindl and Benjamin Leon Bodirsky and Xiaoxi Wang and Lavinia Baumstark and Ulrich Kreidenweis and David Klein and Nele Steinmetz and David Chen and Florian Humpenoeder and Patrick {von Jeetze} and Stephen Wirth and Felicitas Beier and David Hoetten and Pascal Sauer},
   year = {2024},
-  note = {R package version 0.61.2},
-  url = {https://github.com/pik-piam/mrland},
+  note = {R package version 0.62.0},
   doi = {10.5281/zenodo.3822083},
+  url = {https://github.com/pik-piam/mrland},
 }
 ```