**Table 3. Top predictors of interest in migration identified by LASSO Stability Selection**

|**Predictors**|**Appearan**<br>**LASSO(in**|**ce in 1000**<br> **percent)**|**Importa**<br>**from Ran**|**nce rank**<br>**dom Forest**|
|---|---|---|---|---|
||**Women**|**Men**|**Women**|**Men**|
|**_Commonpredictorsfor women and men_**|||||
|Lack of knowledge about Indonesian migrants' expected salary in 6 main destination|||||
|economies (Malaysia; Saudi Arabia; Taiwan, China; Singapore; Hong Kong SAR, China;<br>|100.0|99.9|10|16|
|Brunei Darussalam)|||||
|Respondent doesn't know where to register if interested in working abroad|99.8|98.9|108|106|
|Perceptions of success: Most successful person in the village is international migrant|99.7|100.0|56|81|
|Worked abroad in past 5 years|98.9|98.5|73|103|
|Age|98.1|100.0|7|7|
|Applied to work abroad in the past 5 years|91.0|100.0|144|121|
|Literacy in foreign language other than English|90.2|64.7|103|115|
|<br>Type of work friend/acquaintances are doing abroad: Factory worker|89.6|97.4|76|39|
|Reason why did not travel abroad despite applying: for family reasons other than<br>carin for children|88.6|64.4|153|201|
|g<br>Village Male Labor Force Participation|88.5|99.8|3|3|
|Not married|82.7|60.2|87|76|
|Unemployment within past 12 months|80.4|97.6|93|94|
|Length of migration of latest returning migrant in the household|78.1|73.9|28|56|
|English literacy (reading)|75.0|71.2|62|71|
|No knowledge of number of friends/acquaintances working abroad|73.1|58.1|52|46|
|Respondent has been contacted by broker in past 5 years|67.7|72.7|135|138|
|Knowledge of documents required to work abroad|60.7|76.5|9|12|
|When last abroad, obtained information about opportunities through radio,<br>newspaper,internet|60.2|82.5|121|232|
|**_Predictorsfor women only_**|||||
|Have friends/acquaintances working in: Taiwan, China; Hong Kong SAR, China;|||||
|<br>Singapore|100.0||29||
|Where Respondent applied to work abroad: broker/sponsor|96.0||139||
|Type of work friend/acquaintances are doing abroad: domestic worker|88.9||30||
|Reason why latest returning migrant worked abroad: to follow the success of other|841||185||
|migrant workers|.||||
|<br>Number friends/acquaintances working abroad: more than 10|78.1||94||
|Married|76.6||91||
|Respondent is a wage worker|75.0||150||
|Highest female education in the household (Years of schooling)|64.6||16||
|Not looking for employment because currently awaiting call-back from employer|62.2||214||
|Number of female international migrants in household|62.1||110||
|When Respondent last worked abroad obtained information about opportunities|||||
|,<br>through social network|61.7||105||
|How did latest returning migrant learn about opportunity to work abroad: from<br>family|58.6||141||
|**_Predictorsfor men only_**|||||
|Number of male national migrants in the household||96.4||47|
|Lack of knowledge about Indonesian migrants' type of work in 6 main destination|||||
|economies (Malaysia; Saudi Arabia; Taiwan, China; Singapore; Hong Kong SAR, China;||94.8||18|
|Brunei Darussalam)|||||
|How did latest returning migrant learn about opportunity to work abroad: found||871||212|
|information on their own||.|||
|Main reason why latest returning migrant returned to Indonesia: contract not||865||153|
|renewed||.|||
|<br>Respondent total work income (logged)<br>'||85.6<br>||8<br>|
|PMs migrant network faced issues abroad: long work hours, heavy workload<br>Madurese ethnicity||81.0<br>80.5||215<br>145|
|<br>Respondent has friends/acquaintances currently working abroad||<br>72.9||51|
|Reason why current migrant is working abroad: to earn higher income than possible<br>in Indonesia||71.9||172|
|No knowledge of the risks of working abroad without all the necessary documents||65.5||179|
|Elementary school diploma||65.0||92|
|<br>Monthlyexpected wages abroad relative to village mean income||<br>62.8||1|

Source: Authors’ calculations from DESMIGRATIF (2018). Note: The rank represents the importance of each variable from Random Forest prediction models implemented separately for women and men with 1000 iterations and 327 variables. The rate of appearance in LASSO Stability Selection is obtained from implementing 1000 LASSO iterations with the 327 variables and calculating the occurrence of each variable in each LASSO iteration.

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