Table 4.

Odds ratios from random intercept logistic regression predicting U.S. migration using height and precip. in previous year

	Dry		Mod-Dry		Mod-Wet		Wet
Health & Climate Characteristics
Height (cm)	1.01		0.93	^**	1.08		1.00
Height (cm)	(0.03)		(0.03)		(0.05)		(0.05)
Precip. Year Prior^a	0.92		0.29	^**	3.03		0.77
Precip. Year Prior^a	(0.46)		(0.15)		(2.51)		(0.61)
Height^* Year Prior	1.00		1.01	^**	0.99		1.00
Height^* Year Prior	(0.003)		(0.003)		(0.01)		(0.005)
Demographic & SES Characteristics
Age	0.92	^***	0.93	^***	0.94	^***	0.93	^***
Age	(0.01)		(0.01)		(0.01)		(0.01)
Married	1.20		1.00		1.20		0.94
Married	(0.16)		(0.12)		(0.19)		(0.15)
Years of Education	0.92	^***	0.96	^***	0.99		0.92	^***
Years of Education	(0.02)		(0.01)		(0.02)		(0.02)
HH-Assets	1.10	^***	1.05	^**	1.11	^***	1.18	^***
HH-Assets	(0.03)		(0.02)		(0.04)		(0.04)
Contextual Characteristics
Rural	2.36	^***	1.13		6.28	^***	0.80
Rural	(0.68)		(0.32)		(3.00)		(0.40)
Irrigation Available	1.40		0.90		1.02		0.29	^***
Irrigation Available	(0.63)		(0.30)		(0.86)		(0.13)
Year	1.05	^***	1.01		1.06	^***	1.08	^***
Year	(0.01)		(0.01)		(0.01)		(0.01)
Model Characteristics
Log Likelihood	−2102.94		−2685.53		−1412.49		−1335.50
Person Year Observations	33,794		38,259		47,990		43,730
SD of Constant	0.37	^***	0.38	^***	0.68	^***	0.67	^***
ICC	0.04		0.04		0.12		0.12

S.E. in parentheses

^***

p<0.01

^**

p<0.05

p<0.1

Notes:

Precip. Year Prior variable is modeled using 10-percent increments for ease of interpretation