> But this is obviously not true. Just look at the list of top 10 by GDP and check out how many of them are relatively small.
There absolutely is a correlation between land mass and nominal GDP.
There absolutely is a correlation between land mass and nominal GDP.
| name | gdp_pos | gdp | land_pos | land |
|----------------|---------|----------|----------|---------|
| United States | 1 | 26854599 | 4 | 9147593 |
| China | 2 | 19373586 | 3 | 9596961 |
| Japan | 3 | 4409738 | 62 | 377976 |
| Germany | 4 | 4308854 | 63 | 357114 |
| India | 5 | 3736882 | 7 | 3287263 |
| United Kingdom | 6 | 3158938 | 79 | 242495 |
| France | 7 | 2923489 | 49 | 543940 |
| Italy | 8 | 2169745 | 72 | 301339 |
| Canada | 9 | 2089672 | 2 | 9984670 |
| Brazil | 10 | 2081235 | 5 | 8515767 |
[2] https://en.wikipedia.org/wiki/List_of_countries_and_dependen...
I guarantee that if you plot the countries of the world by GDP and area, you will see a trend line.
It also makes sense. More area = higher chance of larger population and more natural resources. And more space to carry out economic activities with said people and resources.
Edit: I just queried Wolfram Alpha about this. It generated a plot for me, which shows what I expected. Check it out: https://www.wolframalpha.com/input?i=list+of+countries+with+...
Edit2: bonus feature, GPT-4 wrote me a script to plot this also, check it out: https://chat.openai.com/share/ffa45c61-8b7a-44e1-b757-041f31...
There is clearly a correlation, even on linear. It's a little messy, but it's undeniably there.
The starting point for this discussion was about the relationship between a country's size and population and it's power and influence. The correlation between area and GDP demonstrates that there is a meaningful relationship.
Btw, what is your specific complaint about a log-log plot? Country data points for area and GDP span many orders of magnitude, which makes it harder to visualize any patterns on a linear plot.
I also don't understand your point about the dispersion. The correlation and trend is pretty clear. No one said the correlation was 99%.
Edit: I've calculated Pearson's correlation coefficient for this data [1]. The result is 0.82, which indicates a strong positive correlation.
[1] https://en.wikipedia.org/wiki/Pearson_correlation_coefficien...
datamash gave me 0.52 for Pearson. Which is "eh, maybe".
I've reproduced dwaltrib's results using World Bank data on 251 countries, and I get a Pearson's r of 0.82 and a p value of 5.6e-61 (!). I.e. a strong correlation, with high confidence. It makes sense too -- larger countries generally have more people, and more people generally generate more economic activity.
Code if you want to try yourself:
import pandas as pd
gdp = pd.read_csv("~/Downloads/API_NY.GDP.MKTP.CD_DS2_en_csv_v2_5551501.csv").set_index("Country Name")
land_area = pd.read_csv("~/Downloads/API_AG.LND.TOTL.K2_DS2_en_csv_v2_5552158.csv").set_index("Country Name")
gdp["GDP"] = gdp["2020"]
gdp["Land"] = land_area["2020"]
gdp = gdp.dropna(subset=["GDP", "Land"])
from scipy import stats
print(stats.pearsonr(gdp.Land, gdp.GDP))
#+RESULTS: : PearsonRResult(statistic=0.8151313879150333, pvalue=5.621180589722219e-61)