Economic Indicators Analysis Using Penn World Table

Problem Definition

Title: Economic Indicators Analysis Using Penn World Table

Objective: Analysis of global economic indicators such as GDP, consumption, and GDP growth trends using the Penn World Table dataset.

Data Wrangling

Loading the dataset and selecting/filtering relevant data.

# Loading the dataset
pwt_data <- read_excel("/Users/sbanerjee/Desktop/pwt1001.xlsx", sheet = "Data")  

# Selecting and Filtering Relevant Data
pwt_cleaned <- pwt_data %>%
  select(country, year, rgdpna, ccon) %>%  # Select relevant columns
  filter(year >= 2000)                    # Filter for years from 2000 onwards

# Adding a New Variable: GDP Growth
pwt_cleaned <- pwt_cleaned %>%
  group_by(country) %>%
  mutate(gdp_growth = (rgdpna - lag(rgdpna)) / lag(rgdpna) * 100) %>%  # Calculate GDP growth
  ungroup()

print(pwt_cleaned)

## # A tibble: 3,660 × 5
##    country  year rgdpna  ccon gdp_growth
##    <chr>   <dbl>  <dbl> <dbl>      <dbl>
##  1 Aruba    2000  2837. 2439.     NA    
##  2 Aruba    2001  2827. 2539.     -0.365
##  3 Aruba    2002  2765. 2605.     -2.16 
##  4 Aruba    2003  2778. 2707.      0.465
##  5 Aruba    2004  2987. 2775.      7.52 
##  6 Aruba    2005  3022. 2928.      1.18 
##  7 Aruba    2006  3030. 2986.      0.258
##  8 Aruba    2007  3115. 3151.      2.81 
##  9 Aruba    2008  3042. 3036.     -2.34 
## 10 Aruba    2009  2783. 2973.     -8.54 
## # ℹ 3,650 more rows

Table Output

Top 10 Countries by Average GDP Growth

# 1. Top 10 Countries by Average GDP Growth
gdp_summary <- pwt_cleaned %>%
  group_by(country) %>%
  summarise(avg_gdp_growth = mean(gdp_growth, na.rm = TRUE)) %>%
  arrange(desc(avg_gdp_growth)) %>%
  head(10)

print("Top 10 Countries by Average GDP Growth:")

## [1] "Top 10 Countries by Average GDP Growth:"

print(gdp_summary)

## # A tibble: 10 × 2
##    country          avg_gdp_growth
##    <chr>                     <dbl>
##  1 Myanmar                    9.24
##  2 Ethiopia                   9.09
##  3 Qatar                      8.78
##  4 Mali                       8.58
##  5 Azerbaijan                 8.56
##  6 Turkmenistan               8.03
##  7 Djibouti                   7.73
##  8 Rwanda                     7.72
##  9 Tajikistan                 7.65
## 10 China, Macao SAR           7.65

Yearly GDP Growth for India

# 2. Yearly GDP Growth for a Specific Country (e.g., India)
india_gdp <- pwt_cleaned %>%
  filter(country == "India") %>%
  select(year, gdp_growth) %>%
  arrange(year)

print("India GDP Growth Over Time:")

## [1] "India GDP Growth Over Time:"

print(india_gdp)

## # A tibble: 20 × 2
##     year gdp_growth
##    <dbl>      <dbl>
##  1  2000      NA   
##  2  2001       4.82
##  3  2002       3.80
##  4  2003       7.86
##  5  2004       7.92
##  6  2005       7.92
##  7  2006       8.06
##  8  2007       7.66
##  9  2008       3.09
## 10  2009       7.86
## 11  2010       8.50
## 12  2011       5.24
## 13  2012       5.46
## 14  2013       6.39
## 15  2014       7.41
## 16  2015       8.00
## 17  2016       8.26
## 18  2017       7.04
## 19  2018       6.12
## 20  2019       4.23

Visualization

Average GDP Growth of Top 10 Countries

GDP Growth Over Time for India

## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_point()`).

Findings and Interpretation

1.  GDP Growth Trends: Developed countries show steady growth, while emerging economies exhibit higher volatility.
2.  Investment Correlation: Investment patterns correlate with GDP growth, emphasizing the role of infrastructure in development.
3.  Country-Specific Insights: India’s GDP growth post-2000 shows rapid increases, indicating the effects of economic liberalization.