That's weird, are you looking only at the top 10 countries? I've reproduced dwaltrib's results using World Bank data on 251 countries, and I get a Pearson's r

That's weird, are you looking only at the top 10 countries? 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)