## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set(collapse = TRUE, comment = "#>", fig.align = "center", warning = FALSE, screenshot.force = FALSE) ## ---- message=FALSE, warning=FALSE-------------------------------------------- library(concstats) ## ----------------------------------------------------------------------------- data("creditcoops") head(creditcoops) ## ----example-1---------------------------------------------------------------- test_share <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0) test_share_top5 <- concstats_top5(test_share) # top 5 market share in percentage test_share_top5 ## ----example-2---------------------------------------------------------------- test_share <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0) test_share_top <- concstats_mstruct(test_share, type = "top") # top market share test_share_top ## ----examples-mstruct-all----------------------------------------------------- test_share <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0) test_share_mstruct <- concstats_mstruct(test_share, type = "all", digits = 3) test_share_mstruct ## ----examples-entropy, echo=TRUE---------------------------------------------- test_share <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04) test_share_entropy <- concstats_entropy(test_share) test_share_entropy # and as a non-normalized value test_share_entropy2 <- concstats_entropy(test_share, normalized = FALSE) test_share_entropy2 ## ----examples-hhi, echo=TRUE-------------------------------------------------- test_share <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0) test_share_hhi <- concstats_hhi(test_share) test_share_hhi # a normalized value test_share_hhi2 <- concstats_hhi(test_share, normalized = TRUE) test_share_hhi2 # the min average of the hhi test_share_hhi3 <- concstats_comp(test_share, type = "hhi_min") test_share_hhi3 ## ----examples-concstats, echo=TRUE-------------------------------------------- test_share <- c(0.2, 0.3, 0.5) test_share_conc <- concstats_concstats(test_share, digit = 2) test_share_conc ## ----------------------------------------------------------------------------- data("creditcoops") head(creditcoops) ## ----visualization-prep, message=FALSE, eval=FALSE---------------------------- # library(dplyr) # library(kableExtra) ## ----visualization-tab, echo=TRUE, eval=FALSE--------------------------------- # coops_2016 <- creditcoops %>% dplyr::filter(year == 2016) # head(coops_2016) # # coops_2016 <- coops_2016[["total_loans"]] # atomic vector of total loans # coops_2016 <- coops_2016 / sum(coops_2016) # market shares in decimal form # # # We then use the new object `coops_2016` to calculate the market structure # # measures as a group in a one-step-procedure and capture the results in a # # printed table: # coops_2016_mstruct <- concstats_mstruct(coops_2016, type = "all", digits = 2) # coops_2016_mstruct_tab <- coops_2016_mstruct %>% # kableExtra::kbl(caption = "Market structure 2016", digits = 2, # booktabs = TRUE, align = "r") %>% # kableExtra::kable_classic(full_width = FALSE, html_font = "Arial") # coops_2016_mstruct_tab # ## ----visualization-sample-prep, echo=FALSE, eval=FALSE------------------------ # df_shares <- creditcoops %>% # dplyr::select(coop_id, year, paired, total_loans_log) # ## ---- echo=TRUE, eval=FALSE--------------------------------------------------- # library(ggplot2) # Data Visualizations Using the Grammar of Graphics # # df_shares_plot <- df_shares %>% # ggplot(aes(year, total_loans_log, fill = year)) + # geom_boxplot() + # geom_point() + # geom_line(aes(group = paired)) + # labs(title = "Credit cooperatives (type A)", y = "Total loans (log)", # caption = "Source: Andreas Schneider with data from INCOOP") + # theme(legend.position = "none") # df_shares_plot