Merge pull request #258 from USEPA/release-v1.3.0

Release v1.3.0
USEPA · Aug 15, 2023 · 798cd72 · 798cd72
2 parents 169ae5a + a3c5e3b
commit 798cd72
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diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
@@ -4,7 +4,7 @@ name: R CI/CD test #R-CMD-check
 
 on:
   push:
-    branches: [main, master]
+    branches: [main, master, develop]
     paths-ignore:
       - '**.md'  # prevent md files (e.g., README.md) in any repo dir from trigering workflow
       - '**.bib'
@@ -15,7 +15,7 @@ on:
       - '.gitignore'
       - '.gitattributes'
   pull_request:
-    branches: [master] # develop
+    branches: [master, develop]
     paths-ignore:
       - '**.md'
       - '**.bib'

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: useeior
 Type: Package
 Title: USEEIO R modeling software
-Version: 1.2.2
-Date: 2023-7-14
+Version: 1.3.0
+Date: 2023-7-21
 Authors@R: c(
   person("Mo","Li", email="[email protected]", role="aut"),
   person("Wesley","Ingwersen", email="[email protected]", role= c("aut", "cre")),

diff --git a/R/AdjustPrice.R b/R/AdjustPrice.R
@@ -53,8 +53,6 @@ calculateProducerbyPurchaserPriceRatio <- function(model) {
     TWR_CPI <- useeior::Sector_CPI_IO[c("48TW", "42", "44RT"), ]
     TWR_CPI_ratio <- TWR_CPI[, year]/TWR_CPI[, as.character(model$specs$IOYear)]
     TWRValue <- sweep(Margins[, c("Transportation", "Wholesale", "Retail")], 2, TWR_CPI_ratio, "*")
-    # Calculate PurchasersValue
-    PurchasersValue <- rowSums(Margins[, c("ProducersValue", "Transportation", "Wholesale", "Retail")])
     # Generate PRObyPURRatios, or phi vector
     PHI[, year] <- ProducersValue/(ProducersValue + rowSums(TWRValue))
   }
@@ -86,3 +84,22 @@ adjustMultiplierPriceType <- function(matrix, currency_year, model) {
   return(matrix_new)
 }
 
+#' Calculate basic to producer price ratio.
+#' @param model A complete EEIO model: a list with USEEIO model components and attributes.
+#' @return A dataframe of basic to producer price ratio.
+calculateBasicbyProducerPriceRatio <- function(model) {
+  # Get TaxLessSubsidies table
+  TaxLessSubsidies <- merge(model$TaxLessSubsidies, model$Rho,
+                            by.x = "Code_Loc", by.y = 0, all.y = TRUE)
+  TaxLessSubsidies <- TaxLessSubsidies[match(rownames(model$Rho),
+                                             TaxLessSubsidies$Code_Loc), ]
+  # Prepare ratio table Tau using the structure of Rho
+  Tau <- model$Rho
+  for (year in colnames(model$Rho)) {
+    # Adjust BasicValue from model$specs$IOyear to currency year using model$Rho
+    BasicValue <- TaxLessSubsidies$BasicValue * (TaxLessSubsidies[, year]/TaxLessSubsidies[, as.character(model$specs$IOYear)])
+    Tau[, year] <- BasicValue/TaxLessSubsidies$ProducerValue
+  }
+  Tau[is.na(Tau)] <- 1
+  return(Tau)
+}
diff --git a/R/BuildModel.R b/R/BuildModel.R
@@ -117,6 +117,10 @@ constructEEIOMatrices <- function(model) {
   logging::loginfo("Calculating Phi matrix (producer over purchaser price ratio)...")
   model$Phi <- calculateProducerbyPurchaserPriceRatio(model)
 
+  # Calculate basic over producer price ratio.
+  logging::loginfo("Calculating Tau matrix (basic over producer price ratio)...")
+  model$Tau <- calculateBasicbyProducerPriceRatio(model)
+
   #Clean up model elements not written out or used in further functions to reduce clutter
   mat_to_remove <- c("MakeTransactions", "UseTransactions", "DomesticUseTransactions",
                      "UseValueAdded", "FinalDemand", "DomesticFinalDemand",
@@ -223,3 +227,77 @@ createCfromFactorsandBflows <- function(factors,B_flows) {
   return(C)
 }
 
+#' Build an EIO model with economic components only.
+#' @param modelname Name of the model from a config file.
+#' @param configpaths str vector, paths (including file name) of model configuration file
+#' and optional agg/disagg configuration file(s). If NULL, built-in config files are used.
+#' @return A list of EIO model with only economic components
+buildEIOModel <- function(modelname, configpaths = NULL) {
+  model <- initializeModel(modelname, configpaths)
+  model <- loadIOData(model, configpaths)
+  model <- loadDemandVectors(model)
+
+  model$V <- as.matrix(model$MakeTransactions) # Make
+  model$C_m <- generateCommodityMixMatrix(model) # normalized t(Make)
+  model$V_n <- generateMarketSharesfromMake(model) # normalized Make
+  if (model$specs$CommodityorIndustryType=="Industry") {
+    FinalDemand_df <- model$FinalDemandbyCommodity
+    DomesticFinalDemand_df <- model$DomesticFinalDemandbyCommodity
+  } else {
+    FinalDemand_df <- model$FinalDemand
+    DomesticFinalDemand_df <- model$DomesticFinalDemand
+  }
+  model$U <- as.matrix(dplyr::bind_rows(cbind(model$UseTransactions,
+                                              FinalDemand_df),
+                                        model$UseValueAdded)) # Use
+  model$U_d <- as.matrix(dplyr::bind_rows(cbind(model$DomesticUseTransactions,
+                                                DomesticFinalDemand_df),
+                                          model$UseValueAdded)) # DomesticUse
+  colnames(model$U_d) <- colnames(model$U)
+  model[c("U", "U_d")] <- lapply(model[c("U", "U_d")],
+                                 function(x) ifelse(is.na(x), 0, x))
+  model$U_n <- generateDirectRequirementsfromUse(model, domestic = FALSE) #normalized Use
+  model$U_d_n <- generateDirectRequirementsfromUse(model, domestic = TRUE) #normalized DomesticUse
+  model$q <- model$CommodityOutput
+  model$x <- model$IndustryOutput
+  model$mu <- model$InternationalTradeAdjustment
+  if(model$specs$CommodityorIndustryType == "Commodity") {
+    logging::loginfo("Building commodity-by-commodity A matrix (direct requirements)...")
+    model$A <- model$U_n %*% model$V_n
+    logging::loginfo("Building commodity-by-commodity A_d matrix (domestic direct requirements)...")
+    model$A_d <- model$U_d_n %*% model$V_n
+  } else if(model$specs$CommodityorIndustryType == "Industry") {
+    logging::loginfo("Building industry-by-industry A matrix (direct requirements)...")
+    model$A <- model$V_n %*% model$U_n
+    logging::loginfo("Building industry-by-industry A_d matrix (domestic direct requirements)...")
+    model$A_d <- model$V_n %*% model$U_d_n
+  }
+
+  if(model$specs$ModelType == "EEIO-IH"){
+    model$A <- hybridizeAMatrix(model)
+    model$A_d <- hybridizeAMatrix(model, domestic=TRUE)
+  }
+
+  # Calculate total requirements matrix as Leontief inverse (L) of A
+  logging::loginfo("Calculating L matrix (total requirements)...")
+  I <- diag(nrow(model$A))
+  I_d <- diag(nrow(model$A_d))
+  model$L <- solve(I - model$A)
+  logging::loginfo("Calculating L_d matrix (domestic total requirements)...")
+  model$L_d <- solve(I_d - model$A_d)
+
+  # Calculate year over model IO year price ratio
+  logging::loginfo("Calculating Rho matrix (price year ratio)...")
+  model$Rho <- calculateModelIOYearbyYearPriceRatio(model)
+
+  # Calculate producer over purchaser price ratio.
+  logging::loginfo("Calculating Phi matrix (producer over purchaser price ratio)...")
+  model$Phi <- calculateProducerbyPurchaserPriceRatio(model)
+
+  # Calculate basic over producer price ratio.
+  logging::loginfo("Calculating Tau matrix (basic over producer price ratio)...")
+  model$Tau <- calculateBasicbyProducerPriceRatio(model)
+
+  logging::loginfo("EIO model build complete.")
+  return(model)
+}
diff --git a/R/DataDocumentation.R b/R/DataDocumentation.R
@@ -740,3 +740,233 @@
 #'  \item{NAICS_2007_Code}{text code}
 #' }
 "MasterCrosswalk2007"
+
+#' Detail 2012 Supply (2012 schema)
+#' @format A dataframe with 406 obs. and 417 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Detail_Supply_2012"
+
+#' Detail 2012 Use (under the Supply-Use framework, 2012 schema)
+#' @format A dataframe with 414 obs. and 426 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Detail_Use_SUT_2012"
+
+#' Summary 2010 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2010"
+
+#' Summary 2011 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2011"
+
+#' Summary 2012 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2012"
+
+#' Summary 2013 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2013"
+
+#' Summary 2014 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2014"
+
+#' Summary 2015 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2015"
+
+#' Summary 2016 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2016"
+
+#' Summary 2017 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2017"
+
+#' Summary 2018 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2018"
+
+#' Summary 2019 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2019"
+
+#' Summary 2020 Supply (2012 schema)
+#' @format A dataframe with 74 obs. and 83 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Supply_2020"
+
+#' Summary 2010 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2010"
+
+#' Summary 2011 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2011"
+
+#' Summary 2012 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2012"
+
+#' Summary 2013 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2013"
+
+#' Summary 2014 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2014"
+
+#' Summary 2015 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2015"
+
+#' Summary 2016 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2016"
+
+#' Summary 2017 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2017"
+
+#' Summary 2018 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2018"
+
+#' Summary 2019 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2019"
+
+#' Summary 2020 Use (2012 schema)
+#' @format A dataframe with 82 obs. and 92 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Summary_Use_SUT_2020"
+
+#' Sector 2010 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2010"
+
+#' Sector 2011 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2011"
+
+#' Sector 2012 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2012"
+
+#' Sector 2013 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2013"
+
+#' Sector 2014 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2014"
+
+#' Sector 2015 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2015"
+
+#' Sector 2016 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2016"
+
+#' Sector 2017 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2017"
+
+#' Sector 2018 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2018"
+
+#' Sector 2019 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2019"
+
+#' Sector 2020 Supply (2012 schema)
+#' @format A dataframe with 18 obs. and 27 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Supply_2020"
+
+#' Sector 2010 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2010"
+
+#' Sector 2011 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2011"
+
+#' Sector 2012 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2012"
+
+#' Sector 2013 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2013"
+
+#' Sector 2014 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2014"
+
+#' Sector 2015 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2015"
+
+#' Sector 2016 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2016"
+
+#' Sector 2017 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2017"
+
+#' Sector 2018 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2018"
+
+#' Sector 2019 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2019"
+
+#' Sector 2020 Use (2012 schema)
+#' @format A dataframe with 26 obs. and 22 variables
+#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip}
+"Sector_Use_SUT_2020"