## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(knitr) options(scipen = 1, digits = 3) ## ----------------------------------------------------------------------------- library(leontief) X <- transaction_matrix w <- wage_demand_matrix[, "wage"] c <- wage_demand_matrix[, "household_consumption"] d <- wage_demand_matrix[, "final_total_demand"] e <- employment_matrix[, "employees"] ## ----------------------------------------------------------------------------- A <- input_requirement(X, d) A_aug <- augmented_input_requirement(X, w, c, d) rownames(A_aug) <- c(rownames(X), "wage_over_demand") colnames(A_aug) <- c(rownames(X), "consumption_over_demand") kable(A_aug) ## ----------------------------------------------------------------------------- B <- output_allocation(X, d) rownames(B) <- rownames(X) colnames(B) <- rownames(X) kable(B) ## ----------------------------------------------------------------------------- L <- leontief_inverse(A) rownames(L) <- rownames(X) colnames(L) <- rownames(X) kable(L) ## ----------------------------------------------------------------------------- eq <- equilibrium_output(L, d) rownames(eq) <- rownames(X) colnames(eq) <- "output" kable(eq) ## ----------------------------------------------------------------------------- out <- output_multiplier(L) ## ----------------------------------------------------------------------------- inc <- income_multiplier(L, w / d) ## ----------------------------------------------------------------------------- emp <- employment_multiplier(L, e / d) ## ----------------------------------------------------------------------------- sm <- round(cbind(out, inc, emp), 4) rownames(sm) <- rownames(X) colnames(sm) <- c("output_multiplier", "income_multiplier", "employment_multiplier") kable(sm) ## ----------------------------------------------------------------------------- bl <- backward_linkage(A) fl <- forward_linkage(A) bfl <- cbind(bl, fl) rownames(bfl) <- rownames(X) colnames(bfl) <- c("backward_linkage", "forward_linkage") kable(bfl) ## ----------------------------------------------------------------------------- bl <- power_dispersion(L) bl_cv <- power_dispersion_cv(L) bl_t <- cbind(bl, bl_cv) rownames(bl_t) <- rownames(X) colnames(bl_t) <- c("power_dispersion", "power_dispersion_cv") kable(bl_t) ## ----------------------------------------------------------------------------- sl <- sensitivity_dispersion(L) sl_cv <- sensitivity_dispersion_cv(L) sl_t <- cbind(sl, sl_cv) rownames(sl_t) <- rownames(X) colnames(sl_t) <- c("power_dispersion", "power_dispersion_cv") kable(sl_t) ## ----------------------------------------------------------------------------- mp <- multiplier_product_matrix(L) rownames(mp) <- rownames(X) colnames(mp) <- rownames(X) kable(mp) ## ----------------------------------------------------------------------------- bli <- backward_linkage(A_aug) fli <- forward_linkage(A_aug) bfli <- cbind(bli, fli) rownames(bfli) <- c(rownames(X), "wage") # wie = with induced effect colnames(bfli) <- c("backward_linkage_wie", "forward_linkage_wie") kable(bfli)