differ across sub In their explanation for this result they argued that enrolment periods”. ratios have a propensity to rise more in the developing countries, at the same time as growth rates is stagnated or fallen. They also reported that secondary school enrolment contributes positively and significantly to per capita income growth in models where the temporal nature of the human capital variable is dormant. Chapter 4 4.0. Findings and Analysis 4.0.1.Table1. Panel data estimation of African economic growth Explanatory A B C D E F G variables CONSTANT 0.258* 0.336# 0.356# 0.537# 0.528# 0.996# 0.986# (2.405) (3.135) (3.235) (4.064) (4.419) (4.780) (4.302) LGDPINC -0.035* -0.046# -0.049# -0.075# -0.074# -0.116# -0.124# (2.253) (2.788) (2.893) (4.064) (3.898) (4.309) (3.940) AINV 0.139* 0.150* 0.258# 0.240# 0.239# 0.267# (2.488) (2.609) (3.796) (3.246) (2.312) (2.546) POPGRW -0.814& -0.797& -0.668 -0.687 -3.569# -2.582# (1.624) (1.585) (1.205) (1.197) (2.803) (2.055)
differ across sub periods”. In their explanation for this result they argued that enrolment ratios have a propensity to rise more in the developing countries, at the same time as growth rates is stagnated or fallen. They also reported that secondary school enrolment contributes positively and significantly to per capita income growth in models where the temporal nature of the human capital variable is dormant. Chapter 4 4.0. Findings and Analysis 4.0.1.Table1. Panel data estimation of African economic growth Explanatory variables A B C D E F G CONSTANT 0.258* (2.405) 0.336# (3.135) 0.356# (3.235) 0.537# (4.064) 0.528# (4.419) 0.996# (4.780) 0.986# (4.302) LGDPINC -0.035* (2.253) -0.046# (2.788) -0.049# (2.893) -0.075# (4.064) -0.074# (3.898) -0.116# (4.309) -0.124# (3.940) AINV 0.139* (2.488) 0.150* (2.609) 0.258# (3.796) 0.240# (3.246) 0.239# (2.312) 0.267# (2.546) POPGRW -0.814& (1.624) -0.797& (1.585) -0.668 (1.205) -0.687 (1.197) -3.569# (2.803) -2.582# (2.055)
37356-Economic-Growth-in-Africa.docx