PPPs and exchange rates

Data - OECD

Author

Info

source	dataset	.html	.RData
oecd	SNA_TABLE4	2024-06-19	2024-04-30

Data on xrates

source	dataset	.html	.RData
bdf	EXR	2024-06-19	2024-06-18
bis	EER	2024-06-19	2024-05-10
bis	EER_D	2024-06-19	2024-05-10
bis	XRU	2024-05-10	2024-06-07
bis	XRU_D	2024-06-19	2024-05-10
ecb	EXR	2024-06-19	2024-06-15
eurostat	ert_bil_eur_d	2024-06-20	2024-06-08
eurostat	ert_h_eur_d	2024-06-20	2024-06-08
fred	xrates	2024-06-18	2024-06-07
gfd	xrates	2024-06-20	2021-01-08
oecd	REFSERIES_MSIT	2024-06-20	2024-04-30
oecd	SNA_TABLE4	2024-06-19	2024-04-30
wdi	PA.NUS.FCRF	2024-06-20	2024-04-30

Data on industry

source	dataset	.html	.RData
ec	INDUSTRY	2024-06-19	2023-10-01
eurostat	ei_isin_m	2024-06-20	2024-06-08
eurostat	htec_trd_group4	2024-06-20	2024-06-08
eurostat	nama_10_a64	2024-06-20	2024-06-18
eurostat	nama_10_a64_e	2024-06-20	2024-06-18
eurostat	namq_10_a10_e	2024-06-20	2024-06-08
eurostat	road_eqr_carmot	2024-06-20	2024-06-08
eurostat	sts_inpp_m	2024-06-20	2024-06-18
eurostat	sts_inppd_m	2024-06-20	2024-06-08
eurostat	sts_inpr_m	2024-06-20	2024-06-08
eurostat	sts_intvnd_m	2024-06-20	2024-06-08
fred	industry	2024-06-20	2024-06-07
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	2024-06-20	2023-10-04
oecd	SNA_TABLE4	2024-06-19	2024-04-30
wdi	NV.IND.EMPL.KD	2024-01-06	2024-04-14
wdi	NV.IND.MANF.CD	2024-06-20	2024-06-09
wdi	NV.IND.MANF.ZS	2024-01-06	2024-04-14
wdi	NV.IND.TOTL.KD	2024-01-06	2024-04-14
wdi	NV.IND.TOTL.ZS	2024-01-06	2024-04-14
wdi	SL.IND.EMPL.ZS	2024-01-06	2024-04-14
wdi	TX.VAL.MRCH.CD.WT	2024-01-06	2024-04-14

COMPILE_TIME

COMPILE_TIME
2024-06-20

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))