PPPs and exchange rates

Data - OECD


Info

source dataset .html .RData

oecd

SNA_TABLE4

2024-09-11 2024-04-30

Data on xrates

source dataset .html .RData

bdf

EXR

2024-07-26 2024-06-18

bis

EER

2024-08-09 2024-08-28

bis

EER_D

2024-08-28 2024-05-10

bis

XRU

2024-05-10 2024-09-14

bis

XRU_D

2024-08-28 2024-08-28

ecb

EXR

2024-09-14 2024-09-14

eurostat

ert_bil_eur_d

2024-09-14 2024-08-28

eurostat

ert_h_eur_d

2024-09-14 2024-06-08

fred

xrates

2024-09-14 2024-09-14

gfd

xrates

2024-06-20 2021-01-08

oecd

REFSERIES_MSIT

2024-09-15 2024-04-30

oecd

SNA_TABLE4

2024-09-11 2024-04-30

wdi

PA.NUS.FCRF

2024-08-28 2024-09-15

Data on industry

source dataset .html .RData

ec

INDUSTRY

2024-09-15 2023-10-01

eurostat

ei_isin_m

2024-09-14 2024-09-14

eurostat

htec_trd_group4

2024-09-14 2024-09-14

eurostat

nama_10_a64

2024-09-14 2024-09-14

eurostat

nama_10_a64_e

2024-09-14 2024-09-14

eurostat

namq_10_a10_e

2024-09-14 2024-09-14

eurostat

road_eqr_carmot

2024-09-14 2024-09-14

eurostat

sts_inpp_m

2024-06-24 2024-09-14

eurostat

sts_inppd_m

2024-09-15 2024-09-14

eurostat

sts_inpr_m

2024-09-15 2024-09-14

eurostat

sts_intvnd_m

2024-06-24 2024-09-14

fred

industry

2024-09-14 2024-09-14

oecd

ALFS_EMP

2024-04-16 2024-05-12

oecd

BERD_MA_SOF

2024-04-16 2023-09-09

oecd

GBARD_NABS2007

2024-04-16 2023-11-22

oecd

MEI_REAL

2024-05-12 2024-05-03

oecd

MSTI_PUB

2024-09-15 2023-10-04

oecd

SNA_TABLE4

2024-09-11 2024-04-30

wdi

NV.IND.EMPL.KD

2024-01-06 2024-09-15

wdi

NV.IND.MANF.CD

2024-09-15 2024-09-15

wdi

NV.IND.MANF.ZS

2024-01-06 2024-09-15

wdi

NV.IND.TOTL.KD

2024-01-06 2024-09-15

wdi

NV.IND.TOTL.ZS

2024-01-06 2024-09-15

wdi

SL.IND.EMPL.ZS

2024-01-06 2024-09-15

wdi

TX.VAL.MRCH.CD.WT

2024-01-06 2024-09-15

COMPILE_TIME

COMPILE_TIME
2024-09-15

Last

obsTime Nobs
2023 110

TRANSACT

Code
SNA_TABLE4 %>%
  left_join(SNA_TABLE4_var$TRANSACT, by = "TRANSACT") %>%
  group_by(TRANSACT, Transact) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
TRANSACT Transact Nobs
EXC Exchange rates, period-average 4159
EXCE Exchange rates, end of period 3451
PPPGDP Purchasing Power Parities for GDP 2994
PPPPRC Purchasing Power Parities for private consumption 2599
PPPP41 Purchasing Power Parities for actual individual consumption 2051

MEASURE

Code
SNA_TABLE4 %>%
  left_join(SNA_TABLE4_var$MEASURE, by = "MEASURE") %>%
  group_by(MEASURE, Measure) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
MEASURE Measure Nobs
CD National currency per US dollar 15254

LOCATION

Code
SNA_TABLE4 %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  group_by(LOCATION, Location) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Exchange Rate

Flat

Code
include_graphics3b("bib/oecd/SNA_TABLE4_ex1.png")

Javascript

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC") %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  group_by(LOCATION, UNIT, Location) %>%
  summarise(year_first = first(obsTime),
            year_last = last(obsTime),
            `$1 = ` = last(obsValue)) %>%
  ungroup %>%
  mutate(`USD` = paste0("$", round(1/`$1 = `, 3)),
         `EUR` = paste0(round(`$1 = `[UNIT == "EUR"]/`$1 = `, 3), "€"),
         `$1 = ` = paste0(round(`$1 = `, 3), " ", UNIT)) %>%
  select(-UNIT) %>%
  mutate(Loc = gsub(" ", "-", str_to_lower(Location)),
         Loc = paste0('<img src="../../bib/flags/vsmall/', Loc, '.png" alt="Flag">')) %>%
  select(Loc, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

EXC - Period Average: Time Series

Argentina

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION == "ARG") %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("$1 in Argentine Pesos") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 10^seq(-6, 2, 1),
                labels = dollar_format(a = 0.000001, p = "$ ", su = "/$"))

Australia, Austria, Belgium

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION %in% c("AUS", "AUT", "BEL")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  left_join(colors, by = c("Location" = "country")) %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  add_3flags + xlab("") + ylab("Exchange Rate ($1 = ? National Currency)") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 10, 0.1),
                     labels = dollar_format(a = 0.1, p = "", su = " ../$"))

Bulgaria

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION == "BGR") %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("$1 in Bulgarian lev") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(c(0, 0.1, 0.2, 0.3, 0.5, 1, 2, 3), 
                           0.1*c(0, 0.1, 0.2, 0.3, 0.5, 1), 
                           0.01*c(0, 0.1, 0.2, 0.3, 0.5, 1)),
                     labels = dollar_format(a = 0.001, p = "", su = " lev/$"))

Brazil

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION == "BRA") %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("$1 in Brazilian Real") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 10^seq(-6, 2, 1),
                labels = dollar_format(a = 0.000001, p = "", su = " R$/$"))

France, Germany, Italy, Spain, Greece

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION %in% c("FRA", "DEU", "ITA", "ESP", "GRC")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  left_join(colors, by = c("Location" = "country")) %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  add_5flags + xlab("") + ylab("Exchange Rate ($1 = ? National Currency)") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 10, 0.1),
                     labels = dollar_format(a = 0.1, p = "", su = " ../$"))

Canada, United Kingdom

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION %in% c("CAN", "GBR", "DEU")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  left_join(colors, by = c("Location" = "country")) %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  add_3flags + xlab("") + ylab("Exchange Rate ($1 = ? National Currency)") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 10, 0.1),
                     labels = dollar_format(a = 0.1, p = "", su = " ../$"))

Switzerland, United Kingdom

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION %in% c("CHE", "GBR", "DEU")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  left_join(colors, by = c("Location" = "country")) %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  add_3flags + xlab("") + ylab("Exchange Rate ($1 = ? National Currency)") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 10, 0.1),
                     labels = dollar_format(a = 0.1, p = "", su = " ../$"))

Chile

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION == "CHL") %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("$1 in Chilean Peso") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 10^seq(-6, 3, 1),
                labels = dollar_format(a = 0.0001, p = "", su = " CLP/$"))

China

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION == "CHN") %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("$1 in Chinese Yuan") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(1, 10, 1),
                     labels = dollar_format(a = 1, p = "", su = " ¥/$"))

Colombia

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXC",
         LOCATION == "COL") %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("$1 in Colombian Peso") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(5, 10, 20, 30, 50, 
                           100, 200, 300, 500, 
                           1000, 2000, 3000, 5000),
                labels = dollar_format(a = 1, p = "", su = " COL$/$"))

EXCE - End of Period: Time Series

Argentina

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXCE",
         LOCATION == "ARG") %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("$1 in Argentine Pesos") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 10^seq(-6, 2, 1),
                labels = dollar_format(a = 0.000001, p = "$ ", su = "/$"))

Australia, Austria, Belgium

Code
SNA_TABLE4 %>%
  filter(TRANSACT == "EXCE",
         LOCATION %in% c("AUS", "AUT", "BEL")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  left_join(colors, by = c("Location" = "country")) %>%
  year_to_date() %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  add_3flags + xlab("") + ylab("Exchange Rate ($1 = ? National Currency)") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 10, 0.1),
                     labels = dollar_format(a = 0.1, p = "", su = " ../$"))

Individual Countries

Australia

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "PPPPRC", "PPPP41", "EXC"),
         LOCATION %in% c("AUS")) %>%
  year_to_date() %>%
  group_by(date) %>%
  mutate(obsValue = obsValue/obsValue[TRANSACT == "EXC"]) %>%
  filter(TRANSACT != "EXC") %>%
  left_join(SNA_TABLE4_var$TRANSACT, by = "TRANSACT") %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue, color = Transact, linetype = Transact)) + 
  xlab("") + ylab("Purchasing Power Parity") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.4, 0.85),
        legend.title = element_blank())

Austria

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "PPPPRC", "PPPP41", "EXC"),
         LOCATION %in% c("AUT")) %>%
  year_to_date() %>%
  group_by(date) %>%
  mutate(obsValue = obsValue/obsValue[TRANSACT == "EXC"]) %>%
  filter(TRANSACT != "EXC") %>%
  left_join(SNA_TABLE4_var$TRANSACT, by = "TRANSACT") %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue, color = Transact, linetype = Transact)) + 
  xlab("") + ylab("Purchasing Power Parity") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.4, 0.85),
        legend.title = element_blank())

France

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "PPPPRC", "PPPP41", "EXC"),
         LOCATION %in% c("FRA")) %>%
  year_to_date() %>%
  group_by(date) %>%
  mutate(obsValue = obsValue/obsValue[TRANSACT == "EXC"]) %>%
  filter(TRANSACT != "EXC") %>%
  left_join(SNA_TABLE4_var$TRANSACT, by = "TRANSACT") %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue, color = Transact, linetype = Transact)) + 
  xlab("") + ylab("Purchasing Power Parity") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.4, 0.85),
        legend.title = element_blank())

Germany

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "PPPPRC", "PPPP41", "EXC"),
         LOCATION %in% c("DEU")) %>%
  year_to_date() %>%
  group_by(date) %>%
  mutate(obsValue = obsValue/obsValue[TRANSACT == "EXC"]) %>%
  filter(TRANSACT != "EXC") %>%
  left_join(SNA_TABLE4_var$TRANSACT, by = "TRANSACT") %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue, color = Transact, linetype = Transact)) + 
  xlab("") + ylab("Purchasing Power Parity") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.4, 0.85),
        legend.title = element_blank())

Japan

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "PPPPRC", "PPPP41", "EXC"),
         LOCATION %in% c("JPN")) %>%
  year_to_date() %>%
  group_by(date) %>%
  mutate(obsValue = obsValue/obsValue[TRANSACT == "EXC"]) %>%
  filter(TRANSACT != "EXC") %>%
  left_join(SNA_TABLE4_var$TRANSACT, by = "TRANSACT") %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue, color = Transact, linetype = Transact)) + 
  xlab("") + ylab("Purchasing Power Parity") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.6, 0.15),
        legend.title = element_blank())

United States

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "PPPPRC", "PPPP41", "EXC"),
         LOCATION %in% c("USA")) %>%
  year_to_date() %>%
  group_by(date) %>%
  mutate(obsValue = obsValue/obsValue[TRANSACT == "EXC"]) %>%
  filter(TRANSACT != "EXC") %>%
  left_join(SNA_TABLE4_var$TRANSACT, by = "TRANSACT") %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = obsValue, color = Transact, linetype = Transact)) + 
  xlab("") + ylab("Purchasing Power Parity") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.6, 0.15),
        legend.title = element_blank())

PPPGDP/EXC - Purchasing Power Parities for GDP

Table - Relative to U.S.

Javascript

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  group_by(LOCATION, Location) %>%
  summarise(`First Year` = first(obsTime),
            `Last Year` = last(obsTime),
            `Last PPP` = round(last(PPPGDP/EXC),2),
            Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

png

Code
include_graphics3b("bib/oecd/SNA_TABLE4_ex2.png")

United States

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("USA")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = PPPGDP/EXC)) + 
  xlab("") + ylab("Purchasing Power Parity") +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.15, 0.85),
        legend.title = element_blank())

Australia, Austria, Belgium

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("AUS", "AUT", "BEL")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Canada, US, Germany

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("CAN", "USA", "DEU")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Switzerland, Germany, France

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("CHE", "DEU", "FRA")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Denmark, Spain, Finland

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("DNK", "ESP", "FIN")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

France, Greece, United Kingdom

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("FRA", "GBR", "GRC")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Iceland, Ireland, Italy

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("IRL", "ISL", "ITA")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Japan, Luxembourg, Mexico

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("JPN", "LUX", "MEX")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Netherlands, Norway, New Zealand

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("NLD", "NOR", "NZL")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Portugal, Sweden, Turkey

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("PRT", "SWE", "TUR")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

China, India, Korea

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("CHN", "IND", "KOR")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Saudi Arabia, South Africa, Colombia

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("SAU", "ZAF", "COL")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Israel, Indonesia, Germany FFR

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("ISR", "IDN", "DEW")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Chile, Argentina, Brazil

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("CHL", "ARG", "BRA")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Costa Rica, Czech Republic, Poland

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("CRI", "CZE", "POL")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Cabo Verde, Hong Kong, China, Hungary

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("CPV", "HKG", "HUN")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

Morocco, Madagascar, Peru

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPGDP", "EXC"),
         LOCATION %in% c("MAR", "MDG", "PER")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPGDP/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

PPPPRC - Purchasing Power Parities for private consumption

Table

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPPRC", "EXC")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  group_by(LOCATION, Location) %>%
  summarise(`First Year` = first(obsTime),
            `Last Year` = last(obsTime),
            `Last PPP` = round(last(PPPPRC/EXC),2),
            Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Australia, Austria, Belgium

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPPRC", "EXC"),
         LOCATION %in% c("AUS", "AUT", "BEL")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPPRC/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))

PPPP41 - Purchasing Power Parities for actual individual consumption

Table

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPP41", "EXC")) %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  group_by(LOCATION, Location) %>%
  summarise(`First Year` = first(obsTime),
            `Last Year` = last(obsTime),
            `Last PPP` = round(last(PPPP41/EXC),2),
            Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Australia, Austria, Belgium

Code
SNA_TABLE4 %>%
  filter(TRANSACT %in% c("PPPP41", "EXC"),
         LOCATION %in% c("AUS", "AUT", "BEL")) %>%
  year_to_date() %>%
  left_join(SNA_TABLE4_var$LOCATION, by = "LOCATION") %>%
  select(LOCATION, Location, date, TRANSACT, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  mutate(obsValue = PPPP41/EXC) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  na.omit %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Purchasing Power Parity") + add_3flags +
  scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 2, 0.1))