Table 3. Regressions.

	Regression model
	1	2	3	4	5	6	7	8	9
Dependent variables ⇒	Ãn	(T - )	log yn	log yn	log yn	log yn	Quality of institutions	Quality of institutions	log yn
Geography	1.63 (0.08|0.00)						0.628 (0.07|0.00)
log geography		4.71 (0.23|0.00)		2.04 (0.18|0.00)	1.33 (0.39|0.00)	0.527 (0.03|0.06)
(T - ) (1,000s)			0.38 (0.04|0.00)		1.80 (0.63|0.00)	2.50 (0.04|0.00)		5.61 (0.68|0.00)
(T - )2					−0.11 (0.04|0.01)	−0.16 (0.03|0.00)
Quality of institutions						0.037 (0.003|0.00)			0.048 (0.20|0.00)
Adjusted R2	0.79	0.78	0.53	0.52	0.57	0.80	0.43	0.38	0.67

n = 112. The estimator is ordinary linear least-squares. The variables geography, biogeography (Ã_n), thousands of years since the transition to agriculture (T - ), log 1997 GDP per capita (log y_n), and institutions are discussed in the main text. The inflection points implied by the quadratic specifications in (T - ) always exceed the empirical maximum, and therefore the estimated functions are (slightly) concave over their whole range and never backward-bending. In parentheses are SE/P value of coefficient estimates. Regression intercept constants are not reported.