Recovering of economy after 2008 in EU, Finland, and Hungary

library(eurostat)
library(dplyr)
library(ggplot2)
library(directlabels)

clean_eurostat_cache()

# get all EU region data

lp <- get_eurostat_geospatial(output_class = "df", resolution = "20")

# Have an EU-wise overview

lp.eu <- lp %>% filter(STAT_LEVL_ == 0)
lp.eu$NUTS_ID <- droplevels(lp.eu$NUTS_ID)

regions.eu <- levels(lp.eu$NUTS_ID)

estat.eu <- get_eurostat('nama_10r_3gdp',
                         filters = list(unit = 'EUR_HAB',
                                        geo = regions.eu),
                         time_format = 'num',
                         type = 'label')

estat.eu.sel <- estat.eu %>% filter(!is.na(values) & time>=2008) %>%
  select(region = geo, year = time, GDP = values)  %>%
  group_by(region) %>%
  mutate(GDPP = 100*GDP/GDP[1])

# Let's sanitize some country names
levels(estat.eu.sel$region)[grepl("Germany",levels(estat.eu.sel$region))] <- "Germany"
levels(estat.eu.sel$region)[grepl("Macedonia",levels(estat.eu.sel$region))] <- "Macedonia"

ggplot(estat.eu.sel,aes(x=year,y=GDP,color=region)) + geom_line() +
  scale_colour_discrete(guide = 'none') +
  expand_limits(x=2015) +
  geom_dl(aes(label = region), method = "last.qp", cex = 0.4) +
  ggtitle("GDP of regions in Finland\nafter the 2008 crash") +
  labs(x="Year",y="GDP\n[EUR]")

ggplot(estat.eu.sel,aes(x=year,y=GDPP,color=region)) + geom_line() +
  scale_colour_discrete(guide = 'none') +
  expand_limits(x=2015) +
  geom_dl(aes(label = region), method = "last.qp", cex = 0.4) +
  ggtitle("GDP of regions in Finland\nafter the 2008 crash") +
  labs(x="Year",y="GDP\n[% of 2008 GDP]") +
  geom_hline(yintercept=100)

# see on map the winners and loosers

estat.eu.c <- get_eurostat('nama_10r_3gdp',
                           filters = list(unit = 'EUR_HAB',
                                          geo = regions.eu),
                           time_format = 'num')

estat.eu.sel.c <- estat.eu.c %>%
  group_by(geo) %>%
  mutate(GDPP = 100*values/values[9]) %>%
  filter(time==2013) %>%
  select(region = geo, GDPP = GDPP)

estat.eu.sel.c$success <- cut(estat.eu.sel.c$GDPP,
                              breaks =  c(-Inf,100,Inf),
                              labels = c("failure","success"))

lp.eu.gdpp <- left_join(lp.eu %>% filter(lat>36 & long > -12),estat.eu.sel.c,by = c("NUTS_ID" = "region"))


ggplot(lp.eu.gdpp, aes(x=long,y=lat,group=group,fill=success),color="white") + geom_polygon() +
  ggtitle("Recuperation of GDP in EU\nin 2014 to the level in 2008")

ggplot(lp.eu.gdpp, aes(x=long,y=lat,group=group,fill=GDPP),color="white") + geom_polygon() +
  ggtitle("Recuperation of GDP in EU\nin 2014 [% of 2008 GDP]")

# Let's check Finland


lp.fi <- lp %>% filter(grepl('FI',NUTS_ID) & STAT_LEVL_ == 3)
lp.fi$NUTS_ID <- droplevels(lp.fi$NUTS_ID)

#ggplot(lp.fi, aes(x=long,y=lat,group=group,fill=NUTS_ID),color="white") + geom_polygon()

regions.fi <- levels(lp.fi$NUTS_ID)


# NUTS 3 level GDP time series in FI

estat.fi <- get_eurostat('nama_10r_3gdp',
                         filters = list(unit = 'EUR_HAB',
                                        geo = regions.fi),
                         time_format = 'num',
                         type = 'label')

estat.fi.sel <- estat.fi %>% filter(!is.na(values) & time>=2008) %>%
  select(region = geo, year = time, GDP = values)  %>%
  group_by(region) %>%
  mutate(GDPP = 100*GDP/GDP[1])


ggplot(estat.fi.sel,aes(x=year,y=GDP,color=region)) + geom_line() +
  scale_colour_discrete(guide = 'none') +
  expand_limits(x=2015) +
  geom_dl(aes(label = region), method = "last.qp", cex = 0.4) +
  ggtitle("GDP of regions in Finland\nafter the 2008 crash") +
  labs(x="Year",y="GDP\n[EUR]")

ggplot(estat.fi.sel,aes(x=year,y=GDPP,color=region)) + geom_line() +
  scale_colour_discrete(guide = 'none') +
  expand_limits(x=2015) +
  geom_dl(aes(label = region), method = "last.qp", cex = 0.4) +
  ggtitle("GDP of regions in Finland\nafter the 2008 crash") +
  labs(x="Year",y="GDP\n[% of 2008 GDP]") +
  geom_hline(yintercept=100)

# see on map the winners and loosers

estat.fi.c <- get_eurostat('nama_10r_3gdp',
                         filters = list(unit = 'EUR_HAB',
                                        geo = regions.fi),
                         time_format = 'num')

estat.fi.sel.c <- estat.fi.c %>%
  group_by(geo) %>%
  mutate(GDPP = 100*values/values[9]) %>%
  filter(time==2013) %>%
  select(region = geo, GDPP = GDPP)

estat.fi.sel.c$success <- cut(estat.fi.sel.c$GDPP,
                                             breaks =  c(-Inf,100,Inf),
                                             labels = c("failure","success"))

lp.fi.gdpp <- left_join(lp.fi,estat.fi.sel.c,by = c("NUTS_ID" = "region"))


ggplot(lp.fi.gdpp, aes(x=long,y=lat,group=group,fill=success),color="white") + geom_polygon() +
  ggtitle("Recuperation of GDP in Finland\nin 2014 to the level in 2008")

ggplot(lp.fi.gdpp, aes(x=long,y=lat,group=group,fill=GDPP),color="white") + geom_polygon() +
  ggtitle("Recuperation of GDP in Finland\nin 2014 [% of 2008 GDP]")


# Lets repeat for Hungary

lp.hu <- lp %>% filter(grepl('HU',NUTS_ID) & STAT_LEVL_ == 3)
lp.hu$NUTS_ID <- droplevels(lp.hu$NUTS_ID)

regions.hu <- levels(lp.hu$NUTS_ID)


# NUTS 3 level GDP time series in HU

estat.hu <- get_eurostat('nama_10r_3gdp',
                         filters = list(unit = 'EUR_HAB',
                                        geo = regions.hu),
                         time_format = 'num',
                         type = 'label')

estat.hu.sel <- estat.hu %>% filter(!is.na(values) & time>=2008) %>%
  select(region = geo, year = time, GDP = values)  %>%
  group_by(region) %>%
  mutate(GDPP = 100*GDP/GDP[1])


ggplot(estat.hu.sel,aes(x=year,y=GDP,color=region)) + geom_line() +
  scale_colour_discrete(guide = 'none') +
  expand_limits(x=2015) +
  geom_dl(aes(label = region), method = "last.qp", cex = 0.4) +
  ggtitle("GDP of regions in Finland\nafter the 2008 crash") +
  labs(x="Year",y="GDP\n[EUR]")

ggplot(estat.hu.sel,aes(x=year,y=GDPP,color=region)) + geom_line() +
  scale_colour_discrete(guide = 'none') +
  expand_limits(x=2015) +
  geom_dl(aes(label = region), method = "last.qp", cex = 0.4) +
  ggtitle("GDP of regions in Finland\nafter the 2008 crash") +
  labs(x="Year",y="GDP\n[% of 2008 GDP]") +
  geom_hline(yintercept=100)

# see on map the winners and loosers

estat.hu.c <- get_eurostat('nama_10r_3gdp',
                           filters = list(unit = 'EUR_HAB',
                                          geo = regions.hu),
                           time_format = 'num')

estat.hu.sel.c <- estat.hu.c %>%
  group_by(geo) %>%
  mutate(GDPP = 100*values/values[9]) %>%
  filter(time==2014) %>%
  select(region = geo, GDPP = GDPP)

estat.hu.sel.c$success <- cut(estat.hu.sel.c$GDPP,
                              breaks =  c(-Inf,100,Inf),
                              labels = c("failure","success"))

lp.hu.gdpp <- left_join(lp.hu,estat.hu.sel.c,by = c("NUTS_ID" = "region"))


ggplot(lp.hu.gdpp, aes(x=long,y=lat,group=group,fill=success),color="white") + geom_polygon() +
  ggtitle("Recuperation of GDP in Hungary\nin 2014 to the level in 2008")

ggplot(lp.hu.gdpp, aes(x=long,y=lat,group=group,fill=GDPP),color="white") + geom_polygon() +
  ggtitle("Recuperation of GDP in Hungary\nin 2014 [% of 2008 GDP]")