Due note that the R-Squared in the Scatter Plot of Developed Countries its inflated due to presence of outliers in the data. The Spearman Correlation is quite a bit lower than the Pearson Correlation Coefficient of the Developed Countries and is not Statistically Significant as a result (P-Value is >5%). I calculated Spearman Correlations for both the Developed and Developing Countries and only for Developed Countries the Spearman Correlation is much lower than the Pearson Correlation Coefficient whereas for Developing Countries the Spearman Correlation is quite close to the Pearson Correlation Coefficient (Both are Statisically Significant also at the 5% Level for Developing Countries).


My theory is that the difference is due to the fact that many Developing Countries including the one I am living in have a de-facto peg to USD whereas Developed Countries have Market Determined Exchange Rate. Considering Market Exchange Rates have higher volatility than Pegged Exchange Rates this can create bigger deviations from Purchasing Power Parity even over long time horizons but that is just my theory on the matter I cant exactly explain why there is a huge difference here.
Here is link to download the Excel Sheet where I made the scatter plot and calculated the Pearson and Spearman Correlations of the Data.
Thanks.