Problem Definition

Title: Economic Indicators Analysis Using Penn World Table

Objective: Analysis of global economic indicators, including trends in investment, consumption patterns, and population effects on GDP using Penn World Table.

Data Wrangling

Loading the dataset and selecting/filtering relevant data.

# Loading the dataset
pwt_data <- read_excel("/Users/91836/OneDrive/Desktop/pwt1001.xlsx", sheet = "Data")  

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

# Adding a New Variable: GDP Per Capita
pwt_cleaned <- pwt_cleaned %>%
  mutate(gdp_per_capita = rgdpna / pop)  # Calculate GDP per capita

print(pwt_cleaned)
## # A tibble: 3,660 × 7
##    country  year rgdpna  ccon cgdpo    pop gdp_per_capita
##    <chr>   <dbl>  <dbl> <dbl> <dbl>  <dbl>          <dbl>
##  1 Aruba    2000  2837. 2439. 4520. 0.0909         31225.
##  2 Aruba    2001  2827. 2539. 4980. 0.0929         30427.
##  3 Aruba    2002  2765. 2605. 3925. 0.0950         29112.
##  4 Aruba    2003  2778. 2707. 4053. 0.0970         28637.
##  5 Aruba    2004  2987. 2775. 4531. 0.0987         30254.
##  6 Aruba    2005  3022. 2928. 4560. 0.100          30214.
##  7 Aruba    2006  3030. 2986. 4704. 0.101          30050.
##  8 Aruba    2007  3115. 3151. 4544. 0.101          30776.
##  9 Aruba    2008  3042. 3036. 4608. 0.101          30017.
## 10 Aruba    2009  2783. 2973. 4149. 0.101          27427.
## # ℹ 3,650 more rows

Table Output

Top 10 Countries by Average GDP Per Capita

# 1. Top 10 Countries by Average GDP Per Capita
per_capita_summary <- pwt_cleaned %>%
  group_by(country) %>%
  summarise(avg_gdp_per_capita = mean(gdp_per_capita, na.rm = TRUE)) %>%
  arrange(desc(avg_gdp_per_capita)) %>%
  head(10)

print("Top 10 Countries by Average GDP Per Capita:")
## [1] "Top 10 Countries by Average GDP Per Capita:"
print(per_capita_summary)
## # A tibble: 10 × 2
##    country              avg_gdp_per_capita
##    <chr>                             <dbl>
##  1 Qatar                           113068.
##  2 Luxembourg                       86051.
##  3 China, Macao SAR                 77203.
##  4 United Arab Emirates             73968.
##  5 Brunei Darussalam                70953.
##  6 Cayman Islands                   70706.
##  7 Switzerland                      69477.
##  8 Norway                           67253.
##  9 Kuwait                           67080.
## 10 Ireland                          66875.

Yearly Consumption Trends for India

# 2. Yearly Consumption Trends for a Specific Country (e.g., India)
india_consumption <- pwt_cleaned %>%
  filter(country == "India") %>%
  select(year, ccon) %>%
  arrange(year)

print("India Consumption Trends Over Time:")
## [1] "India Consumption Trends Over Time:"
print(india_consumption)
## # A tibble: 20 × 2
##     year     ccon
##    <dbl>    <dbl>
##  1  2000 1868746.
##  2  2001 1978239.
##  3  2002 2031531.
##  4  2003 2156893.
##  5  2004 2278048.
##  6  2005 2513153.
##  7  2006 2683536.
##  8  2007 2964960.
##  9  2008 3228938.
## 10  2009 3515352.
## 11  2010 3865497 
## 12  2011 4291448 
## 13  2012 4623438 
## 14  2013 4747488.
## 15  2014 4937785 
## 16  2015 5254314 
## 17  2016 5581687 
## 18  2017 5886206.
## 19  2018 6325873 
## 20  2019 6608024.

Visualization

Average GDP Per Capita of Top 10 Countries

Consumption Trends Over Time for India

Findings and Interpretation

  1. GDP Per Capita Trends: India has captured a steadily rising consumption curve that has brought into focus the rapidly expanding home market with an improved purchase capacity since 2000.
  2. Consumption Growth: India’s consumption pattern clearly reveals an upward trend in consumption that marks the growth of the increasingly developing domestic economy and increasing purchasing power after 2000.
  3. Population Effects: Per capita GDP translates into the relationship of population dynamics to the economic performance of a country and differences between populous countries and a less populous country.