“The paper discovers a tax structure that optimizes Private Fixed Investments (PFI) in Sub-Saharan Africa (SSA). It applies Data Envelopment Analysis technique to drive a country-by-country and a
year-on-year PFI efficiency scores (for each of the sampled 25 SSA countries, for 2001–12). The scores helped disintegrate observed PFI figures into tax-induced and non-tax-induced subcomponents. Using the efficiency scores, potential PFI at existing tax structure are derived for each country-year pair. Gaps between actual and potential PFIs implied room for PFI growth without maneuvering tax structure (i.e. by changing solely the non-tax determinants of PFI). A panel data
model was then constructed and estimated, under assumed nonlinear association between tax-induced PFI sub-component and tax structure indicators— tax ratio (tax revenue share of GDP) and tax mixes
(tax revenue share of direct, domestic-indirect, and international trade taxes). Using these estimates, tax structures that optimize PFI of each country-year pair are derived. Results reveal that for most of
these countries, ‘tax ratio‘ and ‘revenue share of international trade tax‘ are well below their estimated PFI optimizing levels, while ‘direct-to-domestic-indirect tax mixes‘ are fairly closer. These countries would be better-off, in their PFI, by re-engineering tax ratio and mixes towards estimated PFI optimizing levels. The fact that SSA countries are at best similar (not identical); however, necessitates detailed country level studies for more concrete results.”
