final_project_eda

“tracing EBRD investments in Ukraine”

maps

Graph 1

point: Ukraine has always been one of the most important receiving countries of EBRD investments. Over the whole period (until 2021), Russia has received most investments, followed by Ukraine and Turkey. Looking at the outstanding portfolio positions, Russia has lost its first rank, while Turkey and Ukraine have remained main receivers, joined now by Egypt and Poland.

what happened to France, Kosovo, Norway?

Warning in countrycode_convert(sourcevar = sourcevar, origin = origin, destination = dest, : Some values were not matched unambiguously: Kosovo

call out box does not work

[1] "Call Out Box 1"

EBRD in Ukraine data

# A tibble: 0 × 24
# … with 24 variables: ...1 <dbl>, project_name <chr>, sector <chr>,
#   project_type <chr>, pub_date <date>, project_id <dbl>, country <chr>,
#   project_status <chr>, link <chr>, direct_regional <chr>,
#   original_signing_date <date>, ebrd_finance <dbl>, ebrd_finance_debt <dbl>,
#   ebrd_finance_equity <dbl>, ebrd_finance_guarantee <dbl>,
#   project_status_full <chr>, initiative_date <dttm>, start_date <dttm>,
#   year <dbl>, EUR_per_USD <dbl>, ebrd_finance_USD <dbl>, …

`summarise()` has grouped output by 'sector'. You can override using the
`.groups` argument.

# A tibble: 2 × 24
# Groups:   sector [2]
   ...1 projec…¹ sector proje…² pub_date   proje…³ country proje…⁴ link  direc…⁵
  <dbl> <chr>    <chr>  <chr>   <date>       <dbl> <chr>   <chr>   <chr> <chr>  
1   307 Nak Eme… Natur… State   2022-06-21   53626 Ukraine Repayi… http… Direct 
2   534 Ukrener… Energy State   2022-11-24   54138 Ukraine Disbur… http… Direct 
# … with 14 more variables: original_signing_date <date>, ebrd_finance <dbl>,
#   ebrd_finance_debt <dbl>, ebrd_finance_equity <dbl>,
#   ebrd_finance_guarantee <dbl>, project_status_full <chr>,
#   initiative_date <dttm>, start_date <dttm>, year <dbl>, EUR_per_USD <dbl>,
#   ebrd_finance_USD <dbl>, ebrd_finance_debt_USD <dbl>,
#   ebrd_finance_equity_USD <dbl>, ebrd_finance_guarantee_USD <dbl>, and
#   abbreviated variable names ¹​project_name, ²​project_type, ³​project_id, …

Warning: Removed 24 rows containing missing values (`position_stack()`).

Warning: Removed 15 rows containing missing values (`position_stack()`).

Warning: Removed 12 rows containing missing values (`position_stack()`).

Sector Shares

`summarise()` has grouped output by 'year'. You can override using the
`.groups` argument.

`summarise()` has grouped output by 'year'. You can override using the
`.groups` argument.

# A tibble: 5 × 24
   ...1 projec…¹ sector proje…² pub_date   proje…³ country proje…⁴ link  direc…⁵
  <dbl> <chr>    <chr>  <chr>   <date>       <dbl> <chr>   <chr>   <chr> <chr>  
1   349 Paton    Agrib… Private NA              NA Ukraine <NA>    <NA>  Direct 
2   388 Regiona… Finan… Private 2019-04-29   50744 Ukraine Signed  //ww… Direct 
3   423 Rsf - R… Agrib… Private NA              NA Ukraine <NA>    <NA>  Direct 
4   431 Rsf - U… Agrib… Private NA              NA Ukraine <NA>    <NA>  Direct 
5   433 Rsf - U… Agrib… Private NA              NA Ukraine <NA>    <NA>  Direct 
# … with 14 more variables: original_signing_date <date>, ebrd_finance <dbl>,
#   ebrd_finance_debt <dbl>, ebrd_finance_equity <dbl>,
#   ebrd_finance_guarantee <dbl>, project_status_full <chr>,
#   initiative_date <dttm>, start_date <dttm>, year <dbl>, EUR_per_USD <dbl>,
#   ebrd_finance_USD <dbl>, ebrd_finance_debt_USD <dbl>,
#   ebrd_finance_equity_USD <dbl>, ebrd_finance_guarantee_USD <dbl>, and
#   abbreviated variable names ¹​project_name, ²​project_type, ³​project_id, …

`summarise()` has grouped output by 'year'. You can override using the
`.groups` argument.

`summarise()` has grouped output by 'project_type'. You can override using the
`.groups` argument.

FDI

fin_acc_3 <- fin_acc_subset_2 %>% select(! “fin_acc_item”:“y2000”) %>% pivot_longer( cols = “2001”:“2022”, names_to = “year”, values_to = “investment” )

Direct Investment

fin_acc_4 <- fin_acc_3 %>% filter(grepl(“^1\.[23]”, spec_item)) %>% rename(equity = “1.2_DI_Equity and investment fund shares”)

ggplot(fin_acc_4, aes(x = year, y = investment, fill = spec_item))+ geom_col()

Portfolio Investment

fin_acc_5 <- fin_acc_3 %>% filter(grepl(“^2\.[34]_“, spec_item))

ggplot(fin_acc_5, aes(x = year, y = investment, fill = spec_item))+ geom_col()

Other Investment

fin_acc_6 <- fin_acc_3 %>% filter(spec_item == “4.3_OI_Loans” | spec_item == “4.3.1.3_General government” | spec_item == “4.3.1.3.1_Credit and loans with the IMF”)

ggplot(fin_acc_6, aes(x = year, y = investment, color = spec_item))+ geom_point()

added investments

GDP_data_4 <- GDP_data_3 %>% clean_names() %>% rename(gdp_per_capita_current_usd = “gdp_per_capita_current_us”, gdp_current_usd = “gdp_current_us”)

ggplot(GDP_data_4, aes(x = year, y = gdp_mln_usd)) + geom_line()

ggplot(GDP_data_4, aes(x = year, y = gdp_per_capita_current_usd)) + geom_line()

totals_em <- aggregate(
  cbind(scope_emissions_em$scope_1_excl, scope_emissions_em$scope_2, scope_emissions_em$scope_3, scope_emissions_em$total_exports), by=list(scope_emissions_em$year), FUN = sum) %>% 
  mutate(all_scopes = V1 + V2 + V3) %>% 
  mutate(consumption_total = V1 + V3 - V4) %>% 
  rename(scope_1_total = V1,
         scope_2_total = V2, 
         scope_3_total = V3, 
         year= Group.1
         ) %>% 
  select(!"V4") %>% 
  pivot_longer(
    cols = "scope_1_total":"consumption_total", 
    names_to = "scope", 
    values_to = "total_emissions_per_scope"
  )

Graph 2

EBRD investments over whole period and outstanding portfolio

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