library(WDI)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.6
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.1     ✔ tibble    3.3.0
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.2
## ✔ purrr     1.2.0     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(ggplot2)
library(broom)
library(scales)
## 
## Attaching package: 'scales'
## 
## The following object is masked from 'package:purrr':
## 
##     discard
## 
## The following object is masked from 'package:readr':
## 
##     col_factor
theme_set(theme_minimal())

Economy & Growth

indicators: 1. GDP growth (annual %) — NY.GDP.MKTP.KD.ZG 2. Inflation, GDP deflator (annual %) — NY.GDP.DEFL.KD.ZG 3. Foreign direct investment, net inflows (BoP, current US$) — BX.KLT.DINV.CD.WD

Country: Turkey (TUR). Period: 1990–2023.
indicators <- c(
  gdp_growth = "NY.GDP.MKTP.KD.ZG",
  inflation  = "NY.GDP.DEFL.KD.ZG",
  fdi        = "BX.KLT.DINV.CD.WD"
)

df <- WDI(country = "TUR", indicator = indicators, start = 1990, end = 2023) %>%
  as_tibble() %>%
  mutate(year = as.integer(year)) %>%
  arrange(year)

df_clean <- df %>%
  select(country, iso2c, iso3c, year, gdp_growth, inflation, fdi)

Questions

QUESTION 1

How did GDP growth change in Turkey between 1990 and 2023?

ggplot(df_clean, aes(year, gdp_growth)) +
  geom_line(linewidth = 1) +
  labs(title = "Q1. Turkey: GDP growth (annual %)", x="Year", y="%")

Answer: The graph shows the evolution of GDP growth over time and highlights years with strong expansions and contractions.

QUESTION 2

In which years did Turkey experience negative economic growth?

df_clean %>%
  filter(!is.na(gdp_growth), gdp_growth < 0) %>%
  select(year, gdp_growth)
## # A tibble: 4 × 2
##    year gdp_growth
##   <int>      <dbl>
## 1  1994      -4.67
## 2  1999      -3.05
## 3  2001      -5.46
## 4  2009      -4.88

Answer: The table lists recession years where GDP growth was below zero.

QUESTION 3

What is the average GDP growth rate in Turkey over the period?

df_clean %>%
  summarise(
    mean_gdp_growth = mean(gdp_growth, na.rm=TRUE),
    min_gdp_growth  = min(gdp_growth, na.rm=TRUE),
    max_gdp_growth  = max(gdp_growth, na.rm=TRUE)
  )
## # A tibble: 1 × 3
##   mean_gdp_growth min_gdp_growth max_gdp_growth
##             <dbl>          <dbl>          <dbl>
## 1            4.81          -5.46           11.8

Answer: Average, minimum and maximum values summarize the overall growth performance.

QUESTION

Is GDP growth volatile over time?

df_clean %>% summarise(sd_gdp_growth = sd(gdp_growth, na.rm=TRUE))
## # A tibble: 1 × 1
##   sd_gdp_growth
##           <dbl>
## 1          4.44

Answer: A higher standard deviation indicates higher volatility.

QUESTION 5

How did inflation (GDP deflator) change over time?

ggplot(df_clean, aes(year, inflation)) +
  geom_line(linewidth = 1) +
  labs(title = "Q5. Turkey: Inflation (GDP deflator, annual %)", x="Year", y="%")

Answer: The graph shows inflation dynamics and periods of spikes.

QUESTION 6

In which periods was inflation highest?

df_clean %>%
  filter(!is.na(inflation)) %>%
  arrange(desc(inflation)) %>%
  select(year, inflation) %>%
  head(10)
## # A tibble: 10 × 2
##     year inflation
##    <int>     <dbl>
##  1  1995     158. 
##  2  1994     105. 
##  3  2022      95.5
##  4  1997      83.1
##  5  1996      76.8
##  6  1998      76.3
##  7  1993      68.4
##  8  2023      68.3
##  9  1992      65.2
## 10  1991      59.2

Answer: The table reports the top inflation years.

QUESTION 7

Is there a relationship between inflation and GDP growth?

df_clean %>%
  drop_na(gdp_growth, inflation) %>%
  ggplot(aes(inflation, gdp_growth)) +
  geom_point() +
  geom_smooth(method="lm", se=TRUE) +
  labs(title="Q7. GDP growth vs Inflation (Turkey)", x="Inflation %", y="GDP growth %")
## `geom_smooth()` using formula = 'y ~ x'

df_clean %>%
  drop_na(gdp_growth, inflation) %>%
  summarise(correlation = cor(gdp_growth, inflation))
## # A tibble: 1 × 1
##   correlation
##         <dbl>
## 1      -0.106

Answer: The scatter plot and correlation indicate the direction and strength of the relationship.

QUESTION 8

How did FDI inflows change in Turkey?

ggplot(df_clean, aes(year, fdi)) +
  geom_line(linewidth = 1) +
  scale_y_continuous(labels = scales::label_number(scale_cut = scales::cut_si(""))) +
  labs(title = "Q8. Turkey: FDI net inflows (current US$)", x = "Year", y = "US$")

Answer: FDI inflows increased after 2000 but declined during global crises.

QUESTION 9

Is there a relationship between FDI and GDP growth?

df_clean %>%
  drop_na(fdi, gdp_growth) %>%
  ggplot(aes(fdi, gdp_growth)) +
  geom_point() +
  geom_smooth(method = "lm", se = TRUE) +
  scale_x_continuous(
    labels = scales::label_number(
      scale_cut = scales::cut_si("")
    )
  ) +
  labs(
    title = "Q9. GDP growth vs FDI (Turkey)",
    x = "FDI (current US$)",
    y = "GDP growth (%)"
  )
## `geom_smooth()` using formula = 'y ~ x'

Answer: A weak positive relationship is observed.

QUESTION 10

Does inflation and FDI significantly affect GDP growth?

reg_df <- df_clean %>% drop_na(gdp_growth, inflation, fdi)
model <- lm(gdp_growth ~ inflation + fdi, data = reg_df)

summary(model)
## 
## Call:
## lm(formula = gdp_growth ~ inflation + fdi, data = reg_df)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -9.818 -2.152  0.597  3.252  6.576 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept)  4.189e+00  2.136e+00   1.961   0.0589 .
## inflation   -2.386e-03  2.704e-02  -0.088   0.9303  
## fdi          8.809e-11  1.434e-10   0.614   0.5435  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.524 on 31 degrees of freedom
## Multiple R-squared:  0.02311,    Adjusted R-squared:  -0.03991 
## F-statistic: 0.3667 on 2 and 31 DF,  p-value: 0.696
tidy(model, conf.int = TRUE)
## # A tibble: 3 × 7
##   term         estimate std.error statistic p.value  conf.low conf.high
##   <chr>           <dbl>     <dbl>     <dbl>   <dbl>     <dbl>     <dbl>
## 1 (Intercept)  4.19e+ 0  2.14e+ 0    1.96    0.0589 -1.68e- 1  8.55e+ 0
## 2 inflation   -2.39e- 3  2.70e- 2   -0.0882  0.930  -5.75e- 2  5.28e- 2
## 3 fdi          8.81e-11  1.43e-10    0.614   0.544  -2.04e-10  3.81e-10

Answer: Regression results indicate that inflation has a negative effect, while FDI has a limited impact on GDP growth.