Code
load_data("imf/IFS_M.RData")
load_data("imf/CL_INDICATOR_IFS.RData")
load_data("imf/CL_AREA_IFS.RData")
<- CL_AREA_IFS %>%
iso2c setNames(c("iso2c", "iso2c_desc"))
Data - IMF
load_data("imf/IFS_M.RData")
load_data("imf/CL_INDICATOR_IFS.RData")
load_data("imf/CL_AREA_IFS.RData")
<- CL_AREA_IFS %>%
iso2c setNames(c("iso2c", "iso2c_desc"))
%>%
IFS_M left_join(CL_INDICATOR_IFS, by = "INDICATOR") %>%
group_by(INDICATOR, INDICATOR_desc) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
IFS_M left_join(CL_AREA_IFS, by = c("iso2c" = "AREA")) %>%
group_by(iso2c, AREA_desc) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
IFS_M filter(INDICATOR == "ENDE_XDC_USD_RATE",
%in% c("GB", "FR", "DE")) %>%
iso2c left_join(iso2c, by = "iso2c") %>%
+
ggplot geom_line(aes(x = date, y = value, color = iso2c_desc, linetype = iso2c_desc)) +
theme_minimal() + xlab("") + ylab("Exchange Rate ($1 = ?National Currency)") +
scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_continuous(breaks = seq(0, 10, 1),
labels = dollar_format(accuracy = 0.1, prefix = "", suffix = "../$")) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.8, 0.80),
legend.title = element_blank())
%>%
IFS_M filter(INDICATOR == "EREER_ULC_IX",
%in% c("GB", "FR", "DE", "US")) %>%
iso2c left_join(iso2c, by = "iso2c") %>%
ggplot() +
geom_line(aes(x = date, y = value, color = iso2c_desc, linetype = iso2c_desc)) +
theme_minimal() + xlab("") + ylab("REER based on ULC") +
scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = seq(0, 200, 10),
labels = dollar_format(accuracy = 1, prefix = "")) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.8, 0.2),
legend.title = element_blank())
%>%
IFS_M filter(INDICATOR == "EREER_IX",
%in% c("GB", "FR", "DE", "US")) %>%
iso2c left_join(iso2c, by = "iso2c") %>%
ggplot() +
geom_line(aes(x = date, y = value, color = iso2c_desc, linetype = iso2c_desc)) +
theme_minimal() + xlab("") + ylab("REER based on CPI") +
scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = seq(0, 200, 10),
labels = dollar_format(accuracy = 1, prefix = "")) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.8, 0.80),
legend.title = element_blank())
%>%
IFS_M filter(INDICATOR == "FPE_IX") %>%
left_join(iso2c, by = "iso2c") %>%
group_by(iso2c, iso2c_desc) %>%
summarise(start = first(date),
end = last(date),
Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
IFS_M filter(INDICATOR == "FPE_IX",
%in% c("GB", "FR", "DE", "US")) %>%
iso2c left_join(iso2c, by = "iso2c") %>%
ggplot() +
geom_line(aes(x = date, y = value, color = iso2c_desc, linetype = iso2c_desc)) +
theme_minimal() + xlab("") + ylab("Market Values") +
scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(seq(0, 5, 1), seq(0, 50, 10), seq(0, 200, 50)),
labels = dollar_format(accuracy = 1, prefix = "")) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.8, 0.20),
legend.title = element_blank())
%>%
IFS_M filter(INDICATOR == "FPE_IX",
%in% c("NL", "IT", "GR")) %>%
iso2c left_join(iso2c, by = "iso2c") %>%
ggplot() +
geom_line(aes(x = date, y = value, color = iso2c, linetype = iso2c)) +
theme_minimal() + xlab("") + ylab("Market Values") +
scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(seq(0, 5, 1), seq(0, 50, 10), seq(0, 200, 50)),
labels = dollar_format(accuracy = 1, prefix = "")) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.8, 0.20),
legend.title = element_blank())
%>%
IFS_M filter(INDICATOR == "FPE_IX",
%in% c("JP", "CN")) %>%
iso2c left_join(iso2c, by = "iso2c") %>%
ggplot() +
geom_line(aes(x = date, y = value, color = iso2c, linetype = iso2c)) +
theme_minimal() + xlab("") + ylab("Market Values") +
scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_y_log10(breaks = c(seq(0, 5, 1), seq(0, 50, 10), seq(0, 400, 50)),
labels = dollar_format(accuracy = 1, prefix = "")) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.8, 0.20),
legend.title = element_blank())
%>%
IFS_M filter(INDICATOR == "FPE_IX",
%in% c("JP"),
iso2c >= as.Date("1988-01-01"),
date <= as.Date("1994-01-01")) %>%
date ggplot() + theme_minimal() + xlab("") + ylab("Market Price") +
geom_line(aes(x = date, y = value)) +
scale_x_date(breaks = c(paste0(seq(1950, 2020, 1), "-01-01"),
paste0(seq(1950, 2020, 1), "-07-01")) %>% as.Date,
labels = date_format("%b-%y")) +
scale_y_log10(breaks = c(seq(0, 5, 1), seq(0, 50, 10), seq(0, 400, 10)),
labels = dollar_format(accuracy = 1, prefix = "")) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.8, 0.20),
legend.title = element_blank())