# Computes the transition matrix required in the estimation of the GVAR model ```r Transition_Matrix(t_First, t_Last, Economies, type, DataConnectedness) ``` ## Arguments - `t_First`: character. Sample starting date (format: yyyy). - `t_Last`: character. Sample ending date (format: yyyy). - `Economies`: character vector. Names of the `C` economies included in the system. - `type`: character. Method for computing interdependence. Possible options: * `"Time-varying"`: Computes time-varying interdependence and returns weight matrices for each year. * `"Sample Mean"`: Returns a single weight matrix with average weights over the sample period. * Specific year (e.g., "1998", "2005"): Computes time-invariant interdependence for the specified year. - `DataConnectedness`: list or data frame. Data used to compute the transition matrix (e.g., trade flows). ## Returns matrix or list of matrices. Time-varying or time-invariant transition matrix depending on 'type'. ## Details If there is missing data for any country in a particular year, the transition matrix will include only NAs. ## Examples ```r t_First <- "2006" t_Last <- "2019" Economies <- c("China", "Brazil", "Mexico", "Uruguay") type <- "Sample Mean" # Load data if Connectedness data from excel, otherwise use pre-saved data GetExcelData <- FALSE if (GetExcelData) { if (!requireNamespace("readxl", quietly = TRUE)) { stop( "Please install package \"readxl\" to use this feature.", call. = FALSE ) DataPath <- system.file("extdata", "TradeData.xlsx", package = "MultiATSM") tab_names_Trade <- readxl::excel_sheets(DataPath) list_all_Trade <- suppressMessages(lapply(tab_names_Trade, function(x) { readxl::read_excel(path = DataPath, sheet = x) })) names(list_all_Trade) <- tab_names_Trade L <- length(list_all_Trade) for (i in 1:L) { Countries <- list_all_Trade[[i]][[1]] list_all_Trade[[i]] <- as.data.frame(list_all_Trade[[i]][, -1]) rownames(list_all_Trade[[i]]) <- Countries } DataConnectedness <- list_all_Trade } } else { data(TradeFlows) DataConnectedness <- TradeFlows } W_mat <- Transition_Matrix(t_First, t_Last, Economies, type, DataConnectedness) ```

Transition_Matrix function