# Gather data of several countries in a list. Particularly useful for GVAR-based setups (Compute "GVARFactors") ```r DatabasePrep( t_First, t_Last, Economies, N, FactorLabels, ModelType, Macro_FullData, Yields_FullData, Wgvar = NULL ) ``` ## Arguments - `t_First`: character. Start date of the sample period in the format yyyy-mm-dd. - `t_Last`: character. End date of the sample period in the format yyyy-mm-dd. - `Economies`: character vector. Names of the `C` economies included in the system. - `N`: positive integer. Number of country-specific spanned factors per country. - `FactorLabels`: list. Labels for all variables present in the model, as returned by `LabFac`. - `ModelType`: character. Model type to be estimated. Permissible choices: "JPS original", "JPS global", "GVAR single", "JPS multi", "GVAR multi", "JLL original", "JLL No DomUnit", "JLL joint Sigma". - `Macro_FullData`: list. Full set of macroeconomic data, as returned by `Load_Excel_Data`. - `Yields_FullData`: list. Full set of bond yield data, as returned by `Load_Excel_Data`. - `Wgvar`: GVAR transition matrix. For GVAR models, either a matrix (`C x C`) for fixed weights, or a named list of matrices for time-varying weights. Default is NULL. Required for GVAR models. ## Returns List containing the risk factor set for all countries and global factors. Particularly useful for GVAR-based models. ## General Notation * `C`: number of countries in the system. * `N`: number of country-specific spanned factors. ## Examples ```r # Load data from excel macro_data <- Load_Excel_Data(system.file("extdata", "MacroData.xlsx", package = "MultiATSM")) yields_data <- Load_Excel_Data(system.file("extdata", "YieldsData.xlsx", package = "MultiATSM")) trade_data <- Load_Excel_Data(system.file("extdata", "TradeData.xlsx", package = "MultiATSM")) # Adjust trade data trade_data <- lapply(trade_data, function(df) { countries <- df[[1]] df <- as.data.frame(df[-1]) rownames(df) <- countries df }) # Define features of interest ModelType <- "GVAR multi" Economies <- c("China", "Uruguay", "Russia") GlobalVar <- c("GBC", "CPI_OECD") DomVar <- c("Eco_Act", "Inflation") N <- 3 t0 <- "2006-09-01" tF <- "2019-01-01" # Compute some inputs FactorLabels <- LabFac(N, DomVar, GlobalVar, Economies, ModelType) Wgvar <- Transition_Matrix( t_First = "2006", t_Last = "2019", Economies, type = "Sample Mean", trade_data ) # Compute GVARFactors GVARFactors <- DatabasePrep( t0, tF, Economies, N, FactorLabels, ModelType, macro_data, yields_data, Wgvar ) ```

DatabasePrep function