Table 5.

Random effects logistic estimation of odds of being a migrant in a year—interaction models (data collected from 13 to 41 year olds in 22 villages in Nang Rong, Thailand in 1984–2000)

	Model 1	Model 2	Model 3	Model 4
Individual characteristics
Age	1.03***	1.06***	1.06***	1.32***
Sex (male = 1)	1.32***	1.33***	1.34***	1.75*
Education (in years)	1.35***	1.27***	1.27***	1.82***
Married	0.33***	0.25***	0.25***	0.49**
Land (in rai)	0.999*	0.996***	0.996***	0.973***
Village characteristics
Village remote?	1.06**	1.02	1.01	1.03
Migrant follow-up rate	1.02***	1.02***	1.03***	1.02***
Migration context of the community
Migrant trips in the community	2.11***	27.11***	19.90***	5.60***
Inequality of migrant trips	0.83***	1.29***	0.90	0.94
Thai Economic Context
Unemployment rate (%)	0.89***	0.93***	0.93***	0.93***
Annual GDP growth (%)	1.01***	1.00	1.00	1.00
Productivity-wage gap in agriculture (%)	1.02***	1.01***	1.01***	1.01***
Wage ratio (Bangkok/Northeast)	2.38***	1.58***	1.54***	1.21***
Employment in manufacturing (%)	1.38***	1.20***	1.19***	2.07***
Interactions b/w Ind char and migration experience
Age × trips		0.92***	0.92***	0.95***
Sex × trips		0.80***	0.89**	0.94
Educ × trips		1.00	1.02**	1.08***
Married × trips		0.91***	0.79***	0.87
Land × trips		1.00***	1.01***	1.01***
Interactions b/w Ind char and inequality of mig experience
Age × inequality			1.00	0.99
Sex × inequality			1.14**	1.15**
Educ × inequality			1.03***	1.02*
Married × inequality			0.85**	0.84**
Land × inequality			1.01***	1.01***
Interactions b/w Ind char and economic context
Age × employment in manuf.				0.98***
Sex × employment in manuf.
Educ × employment in manuf.				0.97***
Married × employment in manuf.				0.94**
Land × employment in manuf.				1.00***
Wald χ2	40,435***	41,847***	41,846***	41,909***
N (person-years)	111,668	111,668	111,668	111,668

Year and constant are included in all models. Results are presented in odds ratios. Migration experience and inequality are standardized to mean 0, SD 1

^*p <0.1,

^**p <0.05,

^***p <0.01