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Innovation: Trending Up but needs thrust, especially from the Private Sector 279
Log Population^ 0.495** 0.384**
(0.214) (0.183)
Log GDP per capita (PPP)^ -0.0641 -0.114
(0.0704) (0.0727)
Observations 936 936 936 936 936
Adjusted R-squared 0.960 0.960 0.960 0.960 0.960
Country FE Yes Yes Yes Yes Yes
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
^2019 figures
8.52 Table 2 reports panel Fixed Effects (FE) regression results for dependant variable Log
Knowledge & Technology Output rank for five models with different independent variables -
Log input pillars, Log GDP, Log GDP per capita and Log population. Among the input pillars,
it shows that Log Business Sophistication rank is significant and positively correlated with Log
Knowledge & Technology Output rank, controlling for other pillars, income and population. It
also shows that Log Human Capital & Research rank is significant and negatively correlated with
Log Knowledge & Technology Output rank, controlling for other pillars, income and population.
This suggests the potential for higher business sophistication to lead to better performance in
knowledge & technology outputs.
Table 2: Panel Regression Results: Fixed Effects
Dependant Variable: Log Knowledge & Technology Output rank
(1) (2) (3) (4) (5)
VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5
Log Institutions rank 0.0409 0.0339 0.0287 0.0303 0.0283
(0.0514) (0.0511) (0.0507) (0.0508) (0.0506)
Log HCR rank -0.0935** -0.0948** -0.0920** -0.0938** -0.0919**
(0.0399) (0.0400) (0.0408) (0.0400) (0.0408)
Log Infrastructure rank 0.0204 0.0158 0.0142 0.0142 0.0140
(0.0377) (0.0374) (0.0374) (0.0374) (0.0374)
Log Market Sophistication -0.0220 -0.0215 -0.0196 -0.0205 -0.0194
rank (0.0373) (0.0371) (0.0372) (0.0370) (0.0372)
Log Business Sophistication 0.134*** 0.132*** 0.130*** 0.131*** 0.129***
rank (0.0429) (0.0427) (0.0433) (0.0428) (0.0433)
Log GDP (PPP)^ -0.0666 -0.110
(0.0678) (0.0969)
